Marketing Strategy Market Analysis for axxessio Voice Strategy

Version: 1.0 Status: Completed

Author/Authors: Akshay Deshmukh (AD) Florian Weber (FW) Pratyush Agnihotri (PA) Sascha Peters (SP)

Document History

Version Date Author/-s Remarks/Status

0.1 25.02.2019 AD, FW, PL, PA Initial Draft. 0.2 28.02.2019 FW, PA Review of chapter 1 and 2. 0.3 06.05.2019 AD, FW, PA Chapter 2, 3, 4, 5 and 7 done 0.4 20.05.2019 AD, FW, PA Chapter 1, 5.2 and 6 0.5 21.05.2019 PA Review – Ch. 7, 6, 5 and 4 0.6 23.05.2019 PA Review – Ch. 1 & 2 0.7 24.05.2019 PA Review – Ch. 1, 2, & 3 0.8 27.05.2019 PA Review – correct formatting 0.9 28.05.2019 PA Integration of voice providers 1.0 30.05.2019 PA Change the structure

Table of Contents

1 Summary ...... 5

2 Voice Related Terminology and Definitions ...... 7

2.1 Terms and their Description...... 7 2.2 The relation between Terms and Terminologies ...... 9

3 Understanding the Speech and Voice AI Solutions ...... 10

3.1 How Speech and Voice Recognition Works? ...... 10 3.2 How does chat bot works? ...... 12 3.3 Difference between Voice and ...... 12

4 Opportunities in Speech and Voice Recognition ...... 14

5 Voice Recognition Industry Outlook ...... 18

5.1 Voice Recognition Market Segmentation ...... 18

5.1.1 Market Analysis Based on Regional ...... 18 5.1.2 Smart Speakers Distribution and Usage Study ...... 21 5.1.3 Market Analysis Based on User Needs ...... 24 5.1.4 Market Analysis based on Components, Technology, and Verticals ...... 28 5.1.5 Relevant Market Segments ...... 29

5.2 Voice Solution Providers Landscape ...... 32 5.3 Competitive Landscape – Voice Consulting Firms in Germany ...... 36 5.4 Competitive Landscape – Market Leaders ...... 39

5.4.1 Leaders‘ Market Share ...... 39 5.4.2 Key Points about Leading Players ...... 41 5.4.3 Product Offering of Leading Players ...... 41 5.4.4 Competitive Market Share Analysis...... 42 5.4.5 Competitive Strategy Adopted by Leading Players ...... 42 5.4.6 Analyst View from Leaders’ Competitive Strategy ...... 43

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5.4.7 Recommendation – Key Applications to be Targeted ...... 43 5.4.8 Short Overview of Company’s Profile ...... 44

6 Use Cases for Voice...... 46

7 Go to Market/Marketing ...... 53

References ...... 55

1 Summary

The global voice or speech recognition market is an- ticipated to driven new technological advancements in IT sector. The growing use of voice can be seen as the major industry drivers. Studies demonstrate that the global speech and voice recognition mar- ket size is estimated to reach USD 31.82 billion by 2025, according to a new report by Grand View Re- search, Inc., exhibiting a CAGR of 17.2% during the forecast period. Demand for voice-activated sys- tems, voice-enabled devices, and voice-enabled vir- tual systems is slated to increase over the coming years owing to rising applications in the banking, automobile, finance, logistics sectors. A progressive demand and usage of voice in different industry and application sectors can be seen as a new potential market for axxessio. Although, axxes- sio is not new in the voice market. Our contribution to Smart voice hub (SVH) is exemplary and self-evident about the success of axxessio. However, it becomes significantly important to explore the voice market before stepping ahead and position ourselves as a voice competence company. Therefore, we will answer three relevant questions in this market analysis report which can drive the success of axxessio in the voice sector. In this market analysis, we will be answering:  Q1: What does voice mean for axxessio?  Q2: Where do we stand as a company in a competitive market of voice?  Q3: How do we want to target the relevant market of voice? We have explored and analyzed different use cases, the voice sector, and application areas to answer the first question (Q1). We have compared the analysis result with our existing/required competencies before deciding the meaning of the voice of us. Digital and personal voice assistant, Chat/voice-based application sector can define the meaning of voice for axxessio.

To answer the Q2 and Q3, we conducted extensive research referring to verified data sources such as independent studies, government and regulatory published material, technical journals, trade magazines, and data sources. This forms the basis of our voice market analysis. We considered parameters such as a) market drivers and restraints along with their current and expected impacts, b) technological scenario and expected developments, c) end-use industry trends and dynamics, and d) trends in the consumer behavior during our relevant voice market research and competitor analysis. We have assigned weights to these parameters and quantified their market impacts using the weighted average analysis to derive an expected market growth rate. All our estimates and forecasts were verified through exhaustive primary research with Key Industry Participants (KIPs) which typically include a) Market leading companies and b) System integrators and API/software developers.

At the end of our market research, it can be concluded that relevant market segments of voice such as Digital Voice Assistant and Chat/voice bot have great potential and different opportunities to be follow up. axxessio can build its current competencies and target customer in these relevant segments of voice in the near future.

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Conclusion . The overall speech and voice recognition market is estimated to grow from USD 7.5 billion by 2018 to USD 21.5 billion by 2024, at a CAGR of 19.18% during the period of 2019 -2024. . The market growth can be attributed to the high growth potential in healthcare application, growing demand for voice authentication in a mobile banking application, the rapid pro- liferation of multifunctional devices or smart speakers, and growing impact of Al on the accu- racy of speech and voice recognition . The market for on-premises/embedded speech and voice recognition is expected to grow attire highest CAGR during the forecast period. . The US takes the majority share of the global market and will remain the largest market through 2020, based on Canalys forecast. Despite the notable success in the US and Western Europe, China continues to ignore the products of two giants, and . . According to Google UK, 75% of consumers said they search more now as they can use voice search, while 83% of consumers agree that voice capabilities will make it easier to search for things and 89% believe voice will enable users to find things more quickly. . The demand for digital voice assistants is not only increasing but they are also satisfying con- sumers’ wants and needs. Consumers are starting to interact with brands in the same way they interact with people. It’s informal, intuitive and immediate. . The usage of voice assistant was signification higher in Germany in 2016 i.e. approx. 30 million users and it's increasing annually. . As competition intensifies, Chinese vendors will expand their product portfolios to hit more price points and offer a greater range of capabilities. China has massive potential, with more than 450 million households, over three times the number in the US. . Voice-controlled digital assistants like are emerging as a new platform for news, already outstripping smartwatches in the US and UK. . The partnership with Houndify (SoundHound), Luis.ai (), and Nuance can be really profitable as they are the biggest giants in the voice market. However, they are not targeting industries which are looking to develop voice strategy instead of offering voice specific skills. . Snips is at the top preference to become a partner. One of the reason, they provide voice- based AI solution which is private-by-design, decentralized voice assistant technology. Snips solution can compete with existing voice-based solutions and has great potential. . The top seven companies in the voice recognition market, includes Nuance Communication, Amazon.com Inc., Google Inc. Apple Inc., Microsoft Corporation, IBM Corp. and Baidu Inc. These companies represent more than 51% of the market share in the software space. Nuance communication dominates the market accounting 11.1% share of the total voice recognition software market. Apple’s was built by Nuance communication through technological collaboration . Amazon.com Inc., Google Inc., Apple Inc., and Microsoft Corporation are the other prominent players in the voice recognition market. Amazon.com, Inc. has sold a stag- gering 3 million Echo, a voice recognition product globally. Siri and HomeKit have helped Apple Inc. to build a competitive position in this industry. The aforementioned four players have open source their API to developers, which would expand their ecosystem in the near future. . Baidu, Inc. is a notable player in this market that has achieved 95% accuracy in the loud environment with its Wrap-CTC. The company has open source it to developers in 2016. . Nortek, Inc. a home automation company, is expected to be an emerging player in this market with its acquisition of natural language processing platform, Nuiku, in June 2016. . Industries such as finance, insurance, retail, logistic, healthcare, automobile, traveling, etc have great opportunities to embed and implement voice specific use cases. . In the end, Digital Voice Assistant and Chat/voice bot have great potential and different oppor- tunities to be follow up and axxessio can build its current competencies in this direction.

2 Voice Related Terminology and Definitions

We have provided short definitions of terms and terminologies related voice that we will be using throughout this document. These terminologies definitions will assist to understand the similarity and difference between them. Most importantly, it will provide a broad overview of how they are related to each other.

2.1 Terms and their Description

Description Abbreviation Natural Language Processing (NLP) Machine’s ability to recognize what is said to it, under- stand its meaning, determine the proper action, and re- spond in language the user will understand. NLP = NLU/NLI + NLG Natural Language Understanding Attempts to understand the intended meaning of lan- (NLU) / Natural Language Interpreta- guage and its complexity which are possessed by hu- tion (NLI) man speech such as nuances, subtleties, colloquial- isms, etc. E.g. Alexa, Siri, and Natural Language Generation (NLG) Processes turn structured data into text. (AI) The capability of a machine to imitate intelligent human behavior [9]. Machine Learning (ML) The scientific study of algorithms and statistical models that computer systems use to effectively perform a spe- cific task without using explicit instructions, relying on patterns and inference instead. It is a subset of artificial intelligence [8]. Deep Learning (DL) Part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Supervised Learning Where you have input variables (x) and an output vari- able (Y) and you use an algorithm to learn the mapping function from the input to the output [18]. Unsupervised Learning Where you only have input data (X) and no correspond- ing output variables. The goal is to get in-depth knowledge of the underlying structure or distribution of the data.[18]. Computation Linguistics The techniques of computer science are applied to the analysis and synthesis of language and speech [19]. Speech Recognition The ability of a machine or program to identify words and phrases in spoken language and convert them to a machine-readable format.[20]. Voice Recognition The ability of a machine or program to receive and in- terpret dictation or to understand and carry out spoken commands. The purpose of voice recognition is to iden- tify the person who is speaking [20].

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Named Entity Recognition (NER) / It is a subtask of information extraction that seeks to lo- Entity Identification/ Entity Chunking/ cate and classify named entity mentions in unstruc- Entity Extraction tured text into pre-defined categories such as the per- son names, organizations, locations, medical codes, time expressions, etc. [21] Part of Speech Tagging (POS) Piece of software that reads the text in some language and assigns parts of speech to each word [22]. Text Categorization/ Text Classifica- Text classification is a process of extracting generic tion tags from unstructured text [23] Conference Resolution The task of finding all expressions that refer to the same entity in a text [24]. Machine Translation/ Automated The translation of the text by a computer, with no hu- Translation/ Instant Translation man involvement. Also referred to as [25]. Syntactic Parsing The task of recognizing a sentence and assigning a syntactic structure to it [26] Relation Extraction The task of extracting semantic relationships from a text [27]. Semantic Parsing The process of mapping a natural-language sentence into a formal representation of its meaning. [28]. (QA) It is concerned with building systems that automatically answer questions posed by humans in a natural lan- guage [29]. Paraphrases & Natural Language In- It can transform queries in natural language into Bool- terface ean queries, expanding them with possible ways of combining and paraphrasing [30]. Sentiment Analysis The automated process of understanding an opinion about a given subject from written or spoken language [31]. Dialogue Agents/ Conversational It is a computer system intended to converse with a hu- Agent (CA) man with a coherent structure [32]. Summarization It is the problem of creating a short, accurate, and fluent summary of a longer text document. [33]. Chat Bot/ Smart Bot/ Talk Bot/ Chat- It is a computer program or an artificial intelli- terbot/ Bot/ IM Bot/ Interactive gence which conducts a conversation via auditory or Agent/ Conversational Inter- textual methods [34]. face/ Conversational AI/ Artificial Conversational Entity Virtual Digital Assistant (VDA)/ Intelli- It is a software agent that can perform tasks or services gent Personal Assistant for an individual based on verbal commands [35]. (VUI) It allows people to use voice input to control computers and devices [36]. Voice Assistant It is a digital assistant that uses voice recognition, nat- ural language processing, and to pro- vide aid to users. For example, Siri, Alexa, etc.

2.2 1The relation between Terms and Terminologies

AI

Artificial Intelligence (AI) ML Machine Learning (ML)

DL Deep Learning (DL)

Figure 29: Relation between AL, ML and DL

9

Figure 30: Relation between NLP, NLU, ASR, and TTS

1 Source: Relation between AI, ML, DL, and ADS: https://www.quora.com/Which-jobs-are-growing-for-the-IT-industry-other-than-programming

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3 Understanding the Speech and Voice AI Solutions

In this chapter, we have provided an understanding of how speech and voice AI solutions work followed by the difference between speech and voice recognition solutions. We have discussed and provided a detailed overview of Artificial Intelligence (AI) and Machine Learning (ML) and other voice specific topics in a separate technical document.

3.1 How Speech and Voice Recognition Works?

The workflow of NLP and Speech Recognition:2

Figure 31: Workflow of NLP and Speech Recognition

Spoken language comes to life through acoustic signals. To make sense of what a user is saying you have first to transcribe their speech into text. This process is typically referred to as speech recognition, abbreviated as ASR (“Automatic Speech Recognition”). The output of this step is text. The process of converting speech into text is a sole a transcription step – the computer knows (“recognizes”) the words you said, but it doesn’t yet know what to do with these words. We are missing a huge step to enable a computer to engage in meaningful dialog with us: the act of understanding what the user is saying. That phase is referred to as natural language understand- ing. The output of this step is called a semantic representation, or semantic interpretation.

Assuming that you want the computer to ask about the status of your online order. You could say “where is my order”, “track my package”, “order status”, “status of my shipment”, or any other sequence of words of an almost infinite number of ways to combine words. While the variations of how to express something can be infinite, the things you want to achieve are finite, e.g. in the domain of customer service. Figure 31 represents the workflow of speech recognition.

The workflow of Voice Recognition:3

2 Source: https://blogs.aspect.com/dont-confuse-speech-recognition-with-natural-language-understanding/ 3 Source: https://www.uniphore.com/blog/2018/03/how-does-voice-biometrics-work

Figure 32: Workflow of Voice Recognition

1) Initially, a person' sample is recorded via biometric software. 2) During voice registration, voice templates are extracted and converted from analog to dig- ital signals. After recording and analyzing the voice of many distinctive characteristics, the sophisticated statistical algorithm creates a voiceprint or biometric model. This model is encrypted and stores then the extracted templates in a so-called database. This entire process happens in the background while the customer is in conversation. 3) When a person speaks subsequently, the system creates a voice model and compares it with the stored sample. The result can be displayed on an operator’s monitor. If it displays successful authentication, the operator does not require any further identification from the person.

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3.2 How does chat bot works?

Figure 33: Workflow of Chatbot

It is important to realize that when building chatbots, the entire step of recognizing speech can be skipped. The user already provides the input in text form. We, therefore, are not dealing with a step that a) requires massive computing power, and b) can produce wrong results, i.e. misrecog- nize words. In the text domain, “what you type is what you get.”

3.3 Difference between Voice and Speech Recognition

Speech recognition and voice recognition are two technologies that have evolved exponentially over the past few years. The major sectors like technology companies, banks, law agencies, and other industries rely largely on these solutions to bring more convenience, enhance security and help law enforcement efforts [13] [14].

Many people confuse the terms voice and speech recognition and use it interchangeably. Both are different applications area, which provides different services and performs in different indus- tries.  Voice Recognition: Voice Recognition also known as Speaker Recognition is a process by which a system recognizes the individual characteristics of one’s voice. The voice acts as the identifier of the person. This system analyses individual characteristics on one’s anatomy in- cluding the size and shape of the mouth and throat, as well as behavior patterns including the pitch of the voice, articulations, accent, speaking style, etc. [11] [12].

 Speech Recognition: Speech Recognition is a process of recognizing one’s speech patterns and turns those patterns into something else such as actions (commands) or words on the screen (dictation). It usually stores the spoken words and converts them to a digital set of words. It is also known as “Automatic Speech Recognition” (ASR), “Computer Speech Recog- nition”, “Speech to Text” (STT) [11] [12].

 Key Differences between Voice Recognition and Speech Recognition:

Voice Recognition Speech Recognition Recognizes who is speaking by Recognizes what is being said and Recognition measuring the voice pattern, converts them into text speaking style and other verbal

Identify the speaker Identify & digitally record what the Purpose speaker is saying and respond ac- cordingly. Biometric aspects of the speaker to Focuses on the vocabulary of what Focus recognize them is being said by the speaker. Then, it turns the words into digital texts.

Huge possibility in the technology It helps us to use automatic transla- world which helps to eliminate tions, healthcare transcription, dicta- Application “user verification” (It is a sort of au- tion, robotics, customer service, dible fingerprint) voice computing

Table 9: Key differences between Voice and Speech Recognition [12]

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4 Opportunities in Speech and Voice Recognition

In order to use Voice Technology, an interface between the machine and the user is needed. Voice User Interfaces (VUIs) allow the user to interact with a system through voice or speech commands. Today's VUIs are quickly becoming more intelligent as they learn the user's language patterns over time and even create their own vocabulary. With the rapidly evolving VUIs, speech functions represent the next major shift in computing. In order to create good VUI, brands need to understand their consumers, what they want from a and, more importantly, what aspects of interacting with Artificial Intelligence (AI) drive them to the absolute brink. There are a number of benefits to a VUI/ Voice personal assistant/ Chat/Voice-bot that other user inter- faces cannot provide.

Benefits for Users Benefits for Customers Hands-free and better convenience Optimization and consulting services Improving performance and productivity Eliminate the barrier of typing Improved concentration Turn frustration into accomplishment Improved customer and user experience Manage communication more effectively Improved connectivity and safety Quickly and easily prepare lesson plans Intelligent conversation-based availability of in- Improve mobile documentation and report- formation ing. Increase engagement Central user administration made easy. Wider user demographics Boost efficiency with customizations. Easy information retrieval Customer service accessibility & inbound call deflection Easily add multi-lingual voice support to help a Decrease operational costs different set of users Simplify Multi-Step Transactions Increase average order value and de- crease abandonment Delightful customer experience Increase customer satisfaction by deliver- ing an Omni-channel experience Unlock Critical Time in Customer Support Energizing your customer engagement

Where Voice Assistants can be used: The advantages of VUIs, namely human-like communication and the effectiveness of direct com- munication, have led to VUI becoming known primarily as personal assistants, also regarded as Voice Assistants. Figure 1 shows that more and more tasks are taken over by Voice Assistants. People become aware of the usage of voice and are getting used to it. The tasks that people do by voice vary from simple tasks like setting up a short reminder to complex tasks like ordering a taxi. In fact, half the users stated that the use of Voice Assistants makes their daily life much easier. 47,7% of respondents stated that Voice Assistants are very well suited for the task of retrieving information from a search engine. 40,6% like the idea of playing songs on the fly with their voice. Having read emails and short messages aloud see 31,4% like a game changer. While the is still on the beginning, 26% can already well imagine controlling their household appliances through their voices.

Share of resondents 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% Retrieve information from search engines 47.7% Be reminded of my personal appointments 45.9% Retrieve weather forecast 45.3% Play music or listen to the radio 40.6% Retrieve traffic information 31.9% Have emails or short messages read aloud 31.4% Control household appliances 25.3% Query sports results 23.6% Order a Taxi 14.2% Order goods 13.8% Other 2.2% None of it 15.2% A) Purpose of digital Voice Assistants

Share of respondents 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0%

Relief in everyday life 49%

Fewer waiting times in hotlines 40.9%

Less time in front of the screen 25.8% Better recommendation on the purchase of goods and services 14.8% Other 1.3%

None of it 22.4%

B) Benefits of the increasing use of Voice Assistants

Figure 1: Purpose and Benefits of Voice Assistants

Challenges of Voice Technologies and Concerns of Customers: While there are clear advantages of voice technologies, people are also concerned about the impact that the widespread use of voice applications can have. Figure 2, represents the common concerns from the increasing use of voice assistants. 58% of respondents are afraid that human contact will decrease and a Voice Assistant cannot replace the human warmth. They are also afraid that their personal needs cannot be addressed by the technology and their individuality gets lost. Another big fear is that the increased use of Voice Assistants will lead to many misun- derstandings between the user and the machine. However, many fears can be traced back to the general progress of technologies. To remember is that an increasingly digitized world means that we may actually be spending more time with our devices than we do with each other. If a voice is beneficial for the user depends on the scenario. The environment can be a serious factor whether the use of Voice Technologies makes sense for the user. When there is an envi- ronment with a high ambient noise level, users tend to avoid voice applications. The high noise environment is a problem for the successful understanding of voice command and the user has to compete against the noise.

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Share of respondents 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% It is becoming more and more difficult to reach a human contact person. 58.6% Everyday life becomes more and more impersonal 58.4%

It comes to many misunderstandings 55.3%

There's gonna be more and more advertising. 30.2%

Other 2.8%

None of it 8.6%

Figure 2: Concerns of the increasing use of Voice Assistants

In addition, a VUI will not be a better solution for every use case and sometimes a Graphical User Interface (GUI) will be more fitting. Users interacting with a GUI tend to have a steady and man- ageable amount of attention required to process the information on the screen. VUI however, demands no attention when not actively interfacing with it, and a high degree of attention when the user asks a question and has to listen for a response. This presents a problem when you use VUI to deliver information that comes back in the form of a list. In a good case scenario, the list may be ten entries long, and by the time you reach the end, you have forgotten what the third entry was. The brain simply is not able to carry that much information at one time.

Opportunities available for axxessio: AI-based voice and speech recognition software is projected to witness a high CAGR during the forecast period owing to the continual development of machine learning techniques and integra- tion of connected devices with personal assistants. According to Grand View Research Inc., the global speech and voice recognition market size is estimated to reach USD 31.82 billion by 2025

Figure 3: Global voice and speech recognition software market share by verticals, 2017 (%)

In addition, the demand for voice-activated systems and services such as voice-enabled devices, and voice-enabled assistant systems are expected to increase over the coming years. It is ex- pected that there will be a rise in the applications using more and more voice assistant. Research results presented in Figure 3, shows that banking, automobile sector, healthcare sectors, etc. have already started using voice assistant for better customer services and productivity. From

Figure 3, it can be inferred that the healthcare sector held the largest share in the voice and speech recognition software market. Similarly, the automobile has also the second largest share in the voice and speech recognition software market. Voice recognition is also a core technology widely used in the automobile sector. The automobile sector is expected to gain momentum in the near future owing to advancements in technology and the emergence of innovative concepts such as autonomous and connected cars. Increasing integration of voice-activated software in next-generation cars is likely to stoke the growth of the market during the forecast period. The growth of speech and voice recognition can be attributed to the high growth potential in other services sector as well.

Figure 4: Speech and voice recognition market, by region (USD billion)

Furthermore, the overall speech and voice recognition market is expected to reach USD 21.5 billion by 2024 from USD 7.5 billion in 2018, at a CAGR of 19.18% (cf. Figure 4). Therefore, it can be concluded that the speech and voice market has great potential and opportunities to be unfolded. Research shows the following opportunities in the market.

4The overall speech and voice recognition market is estimated to grow from USD 7.5 billion by 2018 to USD 21.5 billion by 2024, at a CAGR of 19.18% during the forecast period. The market growth can be attributed to the high growth potential in healthcare application, growing demand for voice authentication in a mobile banking application, the rapid proliferation of multifunctional devices or smart speakers, and growing impact of Al on the accuracy of speech and voice recognition The consumer vertical is expected to be dominant in speech and voice recognition market during the forecast period. The market for on-premises/embedded speech and voice recognition is ex- pected to grow attire highest CAGR during the forecast period.

4 https://www.marketsandmarkets.com/Market-Reports/speech-voice-recognition-market-202401714.html

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5 Voice Recognition Industry Outlook

5.1 Voice Recognition Market Segmentation

In this section, market analysis has been performed with respect to voice technology. We have segmented the voice recognition market analysis based on six parameters such as geographic region, distribution, user needs, component, application area, and vertical.

Voice Recognition Market Regional Distribu- User Component Applica- Vertical tion needs tion  Instal-  Market  Hardware  Artificial  Automotive  North America lation share intelli- o U.S.  Software  BFSI o gence o Canada  Manu-  Usage Automatic  Consumer facturer speech  Non-artifi-  Europe  Expec-  Government recognition cial intelli- o UK  Sales tations  Retail o Speaker gence o Germany  Con-  Healthcare verification o France cerns and automa- o Audio min-  Asia Pacific tion ing o Japan  Logistic  Enhanced de- o China  Insurance vices o India  Others o South Korea

Table 1: Voice recognition market segmentation

5.1.1 Market Analysis Based on Regional

The motivation to perform a market analysis on geographical segmentation is to understand how marketers can better serve customers in a particular area. It is also important to know the cus- tomers on a regional level to offer a more personal value proposition that addresses specific topics and needs [37]. Furthermore, the regional study is performed to analyze the voice technol- ogy revenue to understand the growth. The regional study is performed for Worldwide, North America, Asia-pacific, and Europe divisions.

Worldwide - revenue and growth 2015 - 2024

Figure 5 depicts the size of the global market for voice and speech recognition technology, from 2015 to 2024. In 2018, the voice and speech recognition market is estimated to be worth around 1457 million U.S. dollars worldwide and there is a significant growth in the prediction for the up- coming years and expected to reach up to 7124 million U.S. dollars in 2024. This is a huge moti- vation for companies to pursue speech and voice technology as a mainstream.

8000 7,124.97 7000 6000 5,395.2

5000 4,122.78 4000 3,172.03 3000 2,450.26 1,893.51 2000 1,457.22 829.56 1,110

1000 599.9 Revenue in million U.S. dollars U.S. millionin Revenue 0 2015* 2016* 2017* 2018* 2019* 2020* 2021* 2022* 2023* 2024*

Figure 5: Voice and speech recognition technology revenue worldwide 2015-2024

Figure 6 represents the growth of the global market for voice and speech recognition technology, from 2016 to 2024. Even though in the past from 2016 to 2018 there was a slight decline in the growth percentage with an increase in average revenue around 200 million U.S. dollars but from 2020 the growth percentage is predicted to be marginally high compared to its previous years. From the year, 2019 to 2024 there is an increase in the worldwide growth of the revenue from 29.94% to 32.06%. A slight increase in the growth of 2% is being predicted in the coming years.

45.0% 38.28% 40.0% 33.81% 35.0% 31.28% 32.06% 29.94% 29.4% 29.46% 29.97% 30.86% 30.0%

25.0% year growth year

- 20.0% on - 15.0%

10.0% Year 5.0% 0.0% 2016* 2017* 2018* 2019* 2020* 2021* 2022* 2023* 2024*

Figure 6: Voice and speech recognition technology revenue worldwide Growth 2016-2024

Hence, from the above two graphs, we can infer how the worldwide market revenue and overall growth for speech and voice are being performed and prediction for the coming years is a huge influence in the motivation to pursue speech and voice.

North America and Asia-pacific - revenue and growth 2015 - 2024

As we saw how the voice market is growing worldwide over the past few years and the growth forecast for the upcoming years, let us try to understand the market based on a regional segment. Considering U.S.A in our market analysis is very important because of its dominance in the mar- ket from the past few years. Around 78% of households use smart assistants in one or the other form [38]. The applications of smart assistants are no more an alien thing to the Americans.

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Figure 7 shows the size of the North American market for voice and speech recognition technol- ogy, from 2015 to 2024. In 2018, the voice and speech recognition market in North America is estimated to be worth around 380 million U.S. dollars and predicted to reach around 1450 million U.S. dollars by the year 2024, i.e. almost 4 times the current market.

1600 1,457.32 1400 1,169.09 1200 1000 938.09 752.23 800 602.09 dollars 600 480.24 380.89 400 299.46 176.76 232.36 Revenue in million U.S. U.S. millionin Revenue 200 0 2015* 2016* 2017* 2018* 2019* 2020* 2021* 2022* 2023* 2024*

Figure 7: Voice and speech recognition technology revenue in North America 2015-2024

Moving on from North America to the Asia-pacific region, Figure 8 shows the size of the Asia- Pacific market for voice and speech recognition technology, from 2015 to 2024. In 2018, the voice and speech recognition market in the Asia Pacific is estimated to be worth around 436 million U.S. dollars and predicted to reach around 3295 million U.S. dollars by the year 2024 i.e. almost 7 times the current market.

3500 3,295.4 3000 2500 2,327.92 2000 1,656.79 1500 dollars 1,186.31 852.41 1000 612.05 436.17 500 205.37 305.07 Revenue in million U.S. U.S. millionin Revenue 127.93 0 2015* 2016* 2017* 2018* 2019* 2020* 2021* 2022* 2023* 2024*

Figure 8: Voice and speech recognition technology revenue in Asia Specific 2015-2024

European - revenue and growth 2015 - 2024

Figure 9 shows the size of the European market for voice and speech recognition technology, from 2015 to 2024. In 2018, the voice and speech recognition market in Europe is estimated to be worth around 475 million U.S. dollars and predicted to reach around 1650 million U.S. dollars by the year 2024, i.e. 3 times the current market.

1800 1,649.93 1600

1400 1,349.13

1200 1,102.45

1000 899.29

800 731.23 591.56 600 474.95 377.11 400 294.64

Revenue in million U.S. dollarsmillion U.S. inRevenue 224.78 200

0 2015* 2016* 2017* 2018* 2019* 2020* 2021* 2022* 2023* 2024* Figure 9: Voice and speech recognition technology revenue in Europe 2015-2024

Even though voice-enabled devices were introduced at a later stage when compared to the UK and US, the German market has caught its pace. The majority of around 88% of Germans are familiar with voice technology through smartphones, smart speakers, and other devices. Almost 1 in 2 German consumers have ever used voice technology. Most of them have used it on their smartphones (49% of German voice users) whereas only 22% of voice users did so on a smart speaker. Google dominates with respect to smartphone platforms with 68% while Amazon’s Echo is trending for smart speakers with 65% [42]. Similar to the US and Europe, as voice technology acts as a testbed among Germans When we see how young people and young families are embracing the technology, there’s no doubt it will become mainstream.

Hence, from the market walkthrough of speech and voice technology worldwide and all the major regions, we can understand the importance of speech and voice technology, its rapid growth over the years and the quest of demand in the near future.

5.1.2 Smart Speakers Distribution and Usage Study

The proliferation technology that led to the transformation of customer's experience and human interaction is one of the primary factors driving the growth of the global smart speaker market. The leading vendors are leveraging voice-assistance technology that offers ease and conven- ience to end-users to gain a larger global market share.

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Figure 10 demonstrates the market share of manufacturers worldwide from intelligent loudspeak- ers in the year 2017 and 2018. The largest market shares of manufacturers for the year 2017 and 2018 was dominated by Amazon with marginally higher than 80% in the 4th quarter of 2017 with a decline of over half of its share from the previous year with over 35% in the 3rd quarter of 2018. The next big player Amazon made a larger impact on its personal growth in the year 2017 from around 20% in the 1st quarter to around 40% in the 4th quarter. In the year 2018, they started with around 30% of the total market share in the 1st quarter and been in almost the same margin in the 3rd quarter.

Amazon Google Alibaba Baidu Xiaomi Apple Sonos / JBL JD.com Andere 120.0% 100.0% 80.0% 60.0% 40.0%

Anteil am Absatzam Anteil 20.0% 0.0% Q3 2016 Q4 2016 Q1 2017 Q2 2017 Q3 2017 Q4 2017 Q1 2018 Q2 2018 Q3 2018

Figure 10: Market share of manufacturers worldwide of intelligent from Q3 2016 to Q3 2018

Further, when we talk about the US market share for Smart Speakers, Amazon Echo continues to lead market share with 64.6% while Google has made significant market share since 2017 rising to 19.6%. Apple de- buted at 4% market share in May of 2018 after a February launch in the U.S. That fig- ure has risen to 4.5% as Apple has carved out a leadership position in the premium smart speaker segment [39]. Brands other than Amazon Google and Ap- ple constitute a total of 11.3% of the market share for smart speakers. Some of the brands under this category are Sonos, JBL, Bose and Harmon Kardon [39]. The rapid growth of the smart speakers installed base is itself a huge growth driver. When com- pared to the year 2017, there was an enormous growth of over 145% in the year 2018 (Figure 11) [48]. As the installation bases advances in number, the companies can make a more promis- ing stand. In addition, it will determine the speed at which they can appeal to new demographics, move into new industry verticals and gain traction in new countries.

Figure 11: Smart speaker installation base in top five countries

Figure 12 depicts the distribution of worldwide (country-wise) smart speakers installed base in the year 2017 and 2018. The larger installation base of smart speakers in the year 2017 and 2018 was in the United States and China. In the year 2017, around 73% installation base of smart speakers was in the U.S, however, in the next year, there was a decline in the installation base by 9%. China is the second largest installation base with 10% and 8% in the year 2017 and 2018 respectively. Germany had an installation base of 8% in the year 2017 but there was a decline of 2% in the year 2018. However, the rest of the world had an inclination in the installation base of smart speakers from 4% to 10% in the year 2018.

United States China United Kingdom Germany Japan Canada Rest of world

Share of installed base 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% 120.0%

2017* 73%3% 10% 8%3% 2%4%

2018** 64% 10% 8% 6% 10%

Figure 12: Distribution of worldwide smart speakers installed base in 2017 and 2018, by country

Figure 13 demonstrates the forecast for sales of intelligent loudspeakers worldwide in the years 2017 and 2022. In the year 2017, the total sales of intelligent loudspeakers were about 1.5 Billion U.S. Dollar and the forecast of total sales is said to skyrocket with 5.5 Billion U.S. Dollar by the year 2022. This in itself is a huge motivation to pursue Voice in the current market.

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6 5.5 - 5

4

3 Dollar 2 1.5

1 Umsatz in Milliarden US Milliarden in Umsatz 0 2017* 2022*

Figure 13: Forecast for sales of intelligent loudspeakers worldwide in the years 2017 and 2022

From the market study of Smart Speakers, we can see the demand of smart speakers across the globe growing over the years with respect to its installed base and sales. We also saw that rapid growth of big players like Amazon, Google, and apple which reassures the significance of speech and voice technology in today’s market.

5.1.3 Market Analysis Based on User Needs

In this section, we will be discussing the user study of language assistants and smart speakers. The user study has been performed to demonstrate the usage of smart speakers and language assistant worldwide followed by their usage in Germany. Another part of studies performed to demonstrate the users’ voice device preference, their satisfaction, frequent usage and concerns of using language assistants.

Users of a virtual digital assistant in worldwide and Germany

2000 1,831 1,642 1500 1,376 1,016 1000 710 504

500 390 Anzahl in MillioneninAnzahl

0 2015 2016 2017 2018 2019 2020 2021

Figure 14: Prognosis for the use of virtual digital assistants worldwide until 2021

Figure 14, demonstrates that the worldwide usage of the digital assistant was 390 million users in 2015, which has increased drastically by 2019 to 1,376 million users. In comparison to world- wide usage, we can see from Figure 15, the usage of voice assistant was signification higher in Germany in 2016 i.e. approx. 30 million users.

20 17

15 10.8 10 6.8 5

0.8 Anzahl in Millionen in Anzahl 0 Siri Alexa*

Figure 15: Use of language assistants in Germany in 2016

The voice-based AI has evolved significantly and becoming more efficient in this course of time. Therefore, users are increasing annually because of the benefits offered by the voice assistant. Hence, it can be seen from Figure 1 that the worldwide usage and no. of users using voice assis- tant are expected to increase by 2021 and we can project the significant growth in Germany as well by 2021.

Users’ device preference and frequent usage

Anteil der Befragten 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% Smartphone 58% Tablet 20% PC/ Notebook 18% Lautsprecher wie Amazon Echo, Google Home 17% Auto-Infotainmentsystem 12% Smartwatch 6% Kühlschrank 2% Sonstige Geräte 3% Habe ich noch nie genutzt 29% Habe zuvor noch nie von den Sprachassistenten… 1%

Figure 16: Survey on the use of language assistants in Germany by device 2018

Anteil der Befragten 0.0% 5.0% 10.0% 15.0% 20.0% 25.0%

Täglich/ fast täglich 14% An mehreren Tagen in der Woche 19% An einem Tag in der Woche 9% An 2-3 Tagen im Monat 12% An einem Tag im Monat 6% Seltener 20% Habe sie nur mal ausprobiert, ich nutze… 20%

Figure 17: Survey on the frequency of use of language assistants in Germany 2018

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Another part of user study was performed to understand the users’ device preference to use a voice assistant in their daily life. Figure 16, shows that 78% of the users use voice assistance from their mobile devices such as mobile phones and tablets. The percentage of usage of voice assistant is getting lower for non-mobile devices such as , desktop PC, etc. It can be inter- preted that the frequent access of voice assistant can be influenced based on the device prefer- ence of users. In contradictory to this statement, Figure 17 shows a surprisingly different result as there are only 14% of users who preferred to use voice assistant daily while 86% of people use a weekly or monthly basis. From Figure 3, we can conclude that the increase in no. of mobile devices in the future can lead to higher usage of the voice assistant. However, the frequent use can be declined due to the preference of users to use voice assistant i.e. relevance, benefits and concerned of users to use a voice assistant.

Study on users’ concerned, preferred brand and satisfaction of using a voice assistant

We performed users’ satisfaction and concerned study to interpret the users’ preference to use voice assistant frequently followed their preferred voice assistant brand.

Anteil der Befragten 0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% 45.0% 50.0%

Ich habe Sicherheitsbedenken, ungewollt belauscht zu werden 43% Sie sammeln zu viele Daten von mir 39% Ich suche mir Informationen lieber selber heraus, damit ich die Qualität besser einschätzen kann 35% Ich möchte nicht mit Maschinen sprechen 32% Ich weiß nicht, welche Vorteile sie mir bieten könnten, für was ich sie nutzen soll 30% Sie haben aktuell noch zu wenig wirklich nützliche Funktionen für mich 29% Ich möchte nicht, dass meine Stimme aufgezeichnet wird 22% Die Spracherkennung funktioniert noch nicht gut genug 20% Ich weiß nicht wie ich mit den Assistenten sprechen muss, damit sie richtig funktionieren 4% Andere Gründe 4%

Figure 18: Survey on reasons for not using language assistants in Germany 2018

Figure 18 demonstrates the survey on reasons for not using language assistants in Germany in the year 2018. The study shows that the majority of respondents were concerned about their security (43%) and privacy (39%) while using voice assistants. They believed that these virtual assistants used to collect their personal data Another set of respondents were not aware of or satisfied (29%) with the features that language assistance provided them and 4% of the respond- ents did not know how to deal with language assistants. These concerns lack in interest for users to use a voice assistant. The survey presented in Figure 19 demonstrates users’ interest in lan- guage assistants in Germany for the year 2018. According to the survey, 25% of the respondents were not completely interested in using language assistants. Only 13% of the respondents showed complete interest in using language assistants. Around 13% to 15% of the respondents were somewhat neither interested nor disinterested in using language assistants. Hence, it can be inferred that users are more concerned about their privacy and security than convenience which resulted in a lack of interest to use voice assistant frequently in their lives.

30.0% 25% 25.0% 20.0% 15% 15.0% 13% 13% 13% 10% 9% 10.0% 5.0% 1% Anteil derBefragten Anteil 0.0% 1 = Bin 2 3 4 5 6 7 = Bin sehr Weiß nicht überhaupt an einer nicht an Nutzung einer interessiert Nutzung interessiert

Figure 19: Survey on Interest in language assistants in Germany 2018

Even though the market for language assistant has not made a huge impact on users in Germany but popular brands of Smart Speakers are able to make a decent impact among users in Ger- many. Figure 20 depicts the widely used smart speakers in Germany in the year 2017. Amazon Echo (Alexa) dominated with 74% of the market share while Google Home had only 15% of the market share.

Anteil der Befragten 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0%90.0%100.0% Amazon Echo (Alexa) 74% Google Home (Google Assistant) 15% Smart Assistant (Alexa) 6% (Alexa) 5% Sony LF-S50G (Google Assistant) 4% FABRIQ (Alexa) 4% Panasonic SC-GA10 (Google Assistant) 4% Eufy Genie (Alexa) 4% Harman Kardon (Cortana) 3% ILuv Aud Click (Alexa) 2% JBL LINK-Serie (Google Assistant) 2% Zolo Mojo (Google Assistant) 1% Sonstiges 23%

Figure 20: Survey in Germany about popular brands for Smart Speaker 2017

From this, we can infer that the most popular brands of smart speakers in Germany are Amazon Echo (Alexa) and Google Home. One of the reasons, the users are more satisfied with the voice assistant from these brands. From Figure 21, we can notice that users are more satisfied with in comparison to Google assistants, Apple Siri, and Microsoft Cortana.

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Figure 21: Survey on satisfaction with the voice of digital language assistants 2017

Smart Speakers such as Amazon Echo and Google Home are trending at a great pace in Ger- many. As per the studies conducted by Smart Speakers Research Service in August 2018, which involved around 1000 users of smart speakers in Germany [40] [41], 7% of Germans claim to use a smart speaker out of which 43% of those users believe that they “can’t imagine living without” one. Around 61% believe that smart speakers have “greatly improved the way I use technology at home,” and 68% agree, “smart speakers are much more useful than I thought they would be.” The result suggests that smart speakers are set to become widely popular in German homes in the coming years. Other key findings from the study showed that the average number of smart speakers owned by each household is 1.96 (~2). The most popular location for smart speakers in Germany is the living room which constitutes of 71% of the users. Around 21% of the users used the smart speak- ers in kitchen and around 27% of users used it in the bedroom. The most popular uses of smart speakers are listening to music from a streaming music service and getting weather information – 46% of users do this at least once a day. Overall, 85% of Germans are satisfied with their smart speakers. However, their major concern lies the smart speaker’s security and their ability to an- swer any sort of questions [40] [41].

5.1.4 Market Analysis based on Components, Technology, and Verticals

The global voice and speech recognition market size was valued at USD 9.12 billion in 2017. It is poised to expand at a CAGR of 17.2% during the forecast period. Technological advancements along with the rising adoption of advanced electronic devices are projected to stimulate the growth of the market during the forecast period. Voice-activated biometrics used for security purposes help in providing access to authenticated users for performing a transaction. Surging use of voice biometrics is of the key factors driving the market.

Increasing demand for voice-driven navigation systems and workstations is promoting growth in the hardware and software segments. Integration of voice-enabled in-car infotainment systems is gaining popularity across the globe as several countries initiate “hands-free” regulations that gov- ern the use of mobile phones while driving.

Developers of speech and voice recognition market are focusing on innovations, which are esti- mated to accelerate market growth over the forecast period. Use of voice recognition technology in smartphones enable doctors and clinicians to translate their voice into the rich, detailed clinical description, which is recorded in the electronic health record (EHR) system.

The proliferation of voice-enabled IoT devices in smart home automation is expected to work in favor of the market in the near future. IoT-enabled devices would benefit a number of traditionally offline devices with innovative means of user interactions in addition to traditional means such as touch screens and buttons.

Functions Insights

On the basis of functions, the market has been bifurcated into voice recognition and speech recognition. The voice recognition segment has further been divided into speaker identification and speaker verification. Meanwhile, the speech recognition segment has been sub-segmented into automatic speech recognition and text to speech. Further, this technology has been assisting doctors and radiologists in maintaining records of patients. Integration of speech recognition with Virtual Reality (VR) is anticipated to trigger the growth of the overall market. In February 2017, Facebook enhanced its VR platform, Oculus rift, by adding speech recognition to the VR gear of the oculus rift.

Technology Insights

The AI-based technology segment is likely to register a higher CAGR during the forecast period, owing to their ability to recognize patterns of speech accurately. Artificial intelligence exceptionally converts speech into well-structured algorithms by undergoing certain stages, including repre- sentation of speech units, formulation, and development of recognition algorithms along with a demonstration of correct inputs.

Rising development in machine learning and natural language processing is poised to supple- ment the growth of the AI-based technology segment. The rising number of AI-based digital as- sistants such as Alexa and Cortana are projected to stoke the growth of the voice and speech recognition market during the forecast period.

Vertical Insights

The automotive vertical commanded a sizeable share in the market in 2017 owing to increasing incorporation of voice-enabled technologies in-car infotainment systems. Advanced automotive technologies such as connected devices update drivers about traffic conditions on the route and suggest alternative routes.

In 2017, the healthcare sector was at the forefront of the market in terms of revenue. Voice and speech recognition market offers benefits such as reduced report turnaround time and assists doctors in record keeping. As a result, its demand in the sector is anticipated to remain high throughout the forecast horizon.

5.1.5 Relevant Market Segments

In this chapter, we will be discussing the potential market segments for voice technology. Our primary focus will be inclined towards Personal Voice Assistants in particular and Voice bots. The accuracy of speech recognition technology is steadily improving and more services are being added, so that more and more consumers are using voice services, increasing the number of so- called voice-first devices. Some of the results of the survey motivate enough for companies to start engaging in voice control.

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According to the study presented in Figure 21, the number of intelligent loudspeakers used has been increased to around 100 million by the end of 2018. This is almost 2.5 times the size of the end of 2017. In addition, these numbers will continue to grow, more than double by 2020 [50].

Figure 21: Analysis estimates and forecasts, Smart Speaker [50]

Another aspect that is emerging in the voice technology is the amalgamation of conversational interfaces where we will interact with AI bots using chat and voice. They can act as personal assistants and can perform simple tasks such as making phone calls, reading messages, or set- ting alarms and reminders. In retail, bots are primarily used in improvising the user experience. According to the study conducted by Accenture [50], consumers who have in-house digital voice assistance devices are less likely to use their smartphones for entertainment and online shopping. Figure 22 shows the cases in which the Voice First devices are already in use. It shows how voice bots can be integrated with various other services and data delivery channels.

Figure 22: Use cases for Voice First Devices [50]

The demand for voice bots is not only increasing at a great pace but they are also satisfying the consumers’ needs. Consumer’s interaction with brands is at the same level as that of humans, it

is informal, intuitive and immediate. About one in every 5 teens (aged between 14-17) plan to purchase a stand-alone digital voice-enabled assistant in the coming year [49].

Figure 23: Distribution of purchase intent for stand-alone digital voice-enabled assistant devices by age.

The main motivation for using voice bots among users where the advantage of language assis- tants being faster over other methods. In addition, they experienced the language assistants were much easier to use and the output usually provides the user with a satisfactory solution.

According to the study conducted by Capgemini Digital Transformation Institute in 2017 [50], 52% of them felt that using a voice-bot enabled device is more convenient than other means, 48% of them experienced the increase of productivity by doing multi-tasking. 41% of the consumers felt that it satisfied all their personalized needs. And around 38% felt that their data is more secure.

Figure 24: Interactions with standalone digital voice assistants.

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Hence, considering the role that voice- bot enabled devices are playing in the current market, the spread of voice bots will certainly continue to increase and companies should definitely be represented here. Whether it is really the Google Assistant or the Alexa from Amazon. According to research by Raconteur, Google, and Amazon, with Amazon controlling a 71% share of the U.S. market, dominate the voice-enabled smart speaker market. Given their popularity, Amazon Alexa and Google Home are the best products for begin- ners.

Hence, Consumers are ready for new types of interactions with digital devices beyond touchscreens - especially voice control. Conversational user interfaces are shown as one of the top technologies in terms of growth in recent years. Moreover, it promises to continue evolving given the great technological giants are investing in its development. To acquire a real competitive advantage, connected speakers will have to go further than just a wide choice of functions by providing the most personalized user experience possible.

5.2 Voice Solution Providers Landscape

One of the essential components of our market analysis is to do an analysis of our voice solution suppliers. We have focused our analysis to voice assistant market with the aim to analyze com- panies to identify their strengths and weakness. In addition, it is required to identify companies which can be our direct suppliers + potential partners and supplier + competitors. Therefore, we have designed an analysis model that allowed us to evaluate companies based on the same set of criteria. This analysis model combines all of the relevant sources of competitor analysis into one framework in the support of efficient and effective strategy formulation, implementation, mon- itoring, and adjustment. It enabled us to determine companies that are using voice AI to build voice assistant products.

In our competitor analysis model, we used 49 criteria to analyze their general info, strategy, prod- uct portfolio, technology, and financial statuses. These criteria were further assigned to 5 different categories mention in Table 2:

Category Criteria General info Company age or time invested in the industry Company structure & size Trust & brand image Major milestones in company history Strategy Target segments Number of customers/Partners USPs Exemplary support or 24/7 highly responsive support A solid reputable vendor supporting the system

Training services available (On-site training and ongoing customer support Product offer Portfolio Privacy policy & compliant with GDPR Product customizations Pricing model Financial Type of voice solution Technology Multi-Platform Capabilities or Supported Platforms License Security management Multilingual support High Performance and scalability ASR/ STT NLU Wake up word data processing & storage NLG Test to Speech (TTS) Speech recognition Speech to meaning Deep meaning understanding Conversational intelligence Audio & music identification Knowledge graphs Multilingual Text to speech Developer tools Custom commands beamforming echo cancellation emotion detection fingerprint identification automatic language translation voice biometrics Iris recognition Image recognition Face recognition word error rate Documentation / Blog/ Community support/ Technical form Table 2: Criteria for voice solution provider analysis

In addition, every category has a weight to evaluate efficiently the degree of the fulfillment of the criteria. The evaluation based on this scaling allowed us to do segmentation of companies into:  Potential suppliers  Direct & Indirect competitors  Potential customers For example, the criteria “type of customer” belongs to the category “strategy”. The fulfillment of this criterion is rated with a weighting of 0 - 2. Here, the criterion receives a weighting of 0 at the fulfillment level "B2C", 1 for “B2B2C” and 2 for “B2B”. The overall score increases by 2 points in

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the latter case. We focused on companies that deal with voice assistant and rated higher the ones that offer voice AI and generic solution in particular and use machine learning to their products.

Figure 25: Solution providers Analysis The result of the voice supplier analysis is shown in Figure 25. From the figure, it can be seen that the main competitors can be divided into 3 groups:

 Potential Partner (a direct competitor that can be easily transformed into a partner because they are either covering only one link in the value chain or they are a promising innovative startup/ established industry in the field of Voice or speech recognition/ voice assistant/chat or voice bots)  Direct Competitor  Indirect Competitor / Potential Customers (the company that is doing some busi- ness in the area of voice AI services, but not strictly in the area of generic voice solution, and could be interested in integrating our product into their portfolio) rep- resents the list of the main companies that fit in the categories of a potential partner and a direct competitor. You will also find the main strength and weakness of the respective company. Conclusion

Most of the famous solutions are either already bought by a big giant like Cisco, , etc. or focused on a specific industry such as healthcare, automobiles, etc. There are very few suppliers’ solutions which are compliant with GDPR and offer both offline and online processing which gives a competitive advantage in Germany if we decide to do a part- nership with them. Product customizations are equally available in every form and their voice solution can be integrated. However, these voice solution providers are also voice product/application provider as well. Therefore, it becomes necessary to differentiate be- tween suppliers who could be our potential partners or competitors.

The main purpose of identifying the potential partners is to integrate their solution to build voice assistant apps for different industry sectors and enhancing further their solution to develop voice competencies within axxessio. Table 3 shows the list of suppliers which can potential partners and competitors. The list is prepared after extensive research on their profile (cf. Table 2) and arranged in descending order of their importance as a part- ner.

Supplier + Potential partners: Snips, LinTo.ai, Picovoice, Kalliope, Mycraft.ai, wit.ai, Susi.ai, and Leon.ai can be seen as potential partners for axxessio. These companies offer open source voice-based AI solution and they are actively looking for technology and solution partners which can offer them their voice expertise to design, integrate, and enhance their solution. In addition, they are also looking forward to spreading their voice market in Europe.

Supplier + Potential Partners Snips Snips provides Private-By-Design, Decentralized Voice Assistant Tech- nology, and Solutions. LinTo.ai LinTO is a free and Open Source Smart Voice Assistant, designed by LINAGORA. Picovoice Picovoice provides technology and solutions to embed private voice in- terfaces into any product. Kalliope Kalliope is a framework that will help you to create your own personal assistant. Mycraft.ai is a free and open-source voice assistant for Linux-based oper- ating systems that uses a natural language user interface. Wit.ai Open source to build text or voice-based bots Susi.ai Artificial Intelligence for Personal Assistants, Robots, Help Desks and Chatbots. Leon.ai Leon is an open-source personal assistant who can live on your server. Table 3: Identified potential suppliers as partners In this list, Snips is at the top preference to become a partner. One of the reason, they provide voice-based AI solution which is private-by-design, Decentralized Voice Assistant Technology. Snips solution can compete with existing voice-based solutions and has great potential to enhance further. During interviewing them, we found out that their mar- ket strategy completely aligned with our strategy and their technology partnership can assist axxessio to work on Snips development enabling us to build voice-based compe- tencies.

Supplier + Potential Competitors:

Supplier + Competitors Houndify Houndify is the leading innovator in voice-enabled AI technologies. Luis.ai A machine learning-based service to build natural language into apps, bots, and IoT devices. Nuance Design conversational AI that makes daily excellence inevitable.

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Digital Genius AI platform that puts customer support on autopilot by understand- ing conversations, automating repetitive processes and delighting your customers. nVoq nVoq’s main product is SayIt, a speech-to-text solution designed to improve workflow. German Autolabs Building a voice AI platform for the Automotive vertical. Table 4: Identified potential supplier as competitors The partnership with Houndify (SoundHound), Luis.ai (Microsoft), and Nuance can be really profitable as they are the biggest giants in the voice market. These voice providers have really established as well as a product provider for different industries. Moreover, their partnership model is different than the supplier + partnership ones. As, they are targeting industries to develop voice assistant for them and strategically, they are looking for 3rd parties voice solution which can enhance their voice solution capabilities. They are not targeting industries which are looking to develop voice strategy. For such companies, they offer open source API for developers and different licensing model support them. Therefore, I have put them in the list of competitors as axxessio is building voice compe- tencies while these companies have already grown in the voice industry. Other compa- nies such as German Autolabs, nVoq. Digital Genius can be a competitor in specific in- dustries such as automobile, etc. Furthermore, they are not actively looking for technol- ogy-based partnership instead of solution based partnership.

5.3 Competitive Landscape – Voice Consulting Firms in Germany

6 5 5 5 4 4 4 4 3 3 3 3 3 2 2 2

Score 2 1 0

Voice Consulting Firms in Germany

Figure 26: Competitors analysis result of voice consulting firms in Germany We have performed the competitors’ analysis for consulting and voice solution provider within Germany as well. The analysis is performed to answer three main questions – a) What companies are doing specifically in the direction of voice? b) what is their voice solution? and c) How grown and established they are in comparison to axxessio? Figure 26 represents the result of the anal- ysis. Based on companies’ profile analysis, these companies can be divided into three categories – a) Voice + IT Consulting firms, b) Voice only, and c) IT Consulting only. This categorization will assist to do further analysis of these voice solution and consulting companies to identify potential partners and competitors.

Voice-based Competitors and Potential Partners:

 Well established company and focused on innovation  Own voice solution "Aaron.ai" voice solution for web & mobile Aaron  Support another voice assistant such as Alexa, Google, etc. GmbH  The developed smart telephone use case for healthcare  Established customers and partner portfolio  Well established company and focused on innovation and developing voice so- Paragon lutions Semvox  Acquired by Paragon GmbH GmbH  Nuance Speech Recognition & Speech Synthesis embedded for all applications ranging from toy robots to home appliances  Established portfolio in Cloud-based communication, Business voice, Cloud Tenios IVR, Telecom-API  Focused on voice-based AI for the Telecommunication sector  A startup company that offers voice-based AI to identify and understand human psychology.  Focused on offering a speech to text solution or API to analyze the language to Precire understand the human psyche  The solution is relevant only for human interaction app such as customer feed- back apps.  Neo is a digital assistant powered by AI, that automates your routine work: Pre- Neohel- paring meetings, monitoring dashboards, aggregating data, and so much more. den  Startup. Currently, Neo offers digital voice assistant solution, integration and Neo specific voice consulting Table 5: Voice based Competitors and Potential Partners

The first category (cf. Table 5) includes the list of companies which are well established in the voice market such as Aaron and Paragon GmbH. These two companies are focused on innova- tion and providing their voice assistant API or solution for developing voice assistant for web, mobile, desktop, etc. In addition to providing voice solution, these companies are working on Alexa and Google skills kit to develop voice assistant apps as well. Moreover, these companies have a well-established voice specific portfolio to target different industries. From company port- folio point of view, it can be said that the partnership with such companies can be beneficiary for axxessio. However, these companies are enhancing their voice solution and looking for voice experts in the voice market. Moreover, they are independent voice product provider as well which can result in the competition for axxessio with these companies in the later stage.

Another part of the list includes voice based consulting firms which are either startups such as Neohelden or focused on a specific industry such as Tenios (Telecommunication sector) and Precire (human psychology). The partnership can be really useful with Tenios and Precire only if we are looking forward to target only specific industry sector as their solution is not generic voice solution which can be used for other industries as well. In the case of Neohelden, they offer a digital assistant powered by AI, that automates your routine work: preparing meetings, monitor- ing dashboards, aggregating data, and so much more. They are targeting a wide range of indus- tries. Therefore, partnership with them can be really useful as we can use their API to develop use cases and assist them to grow together in the voice market in Germany. Similarly, the part- nership can be done with Precire and Tenios to target specific industry which is aligned with

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these companies’ portfolio. However, all these companies (Precire, Tenios, and Neohelden) are pretty new to their solutions and reliability of these companies are to be questioned.

Voice Consulting based Partners:

 New in industry Consetto  Focused on using voice AI skills from Alexa and Google GmbH  Customer and partner portfolio are not mentioned. Mainly offering voice consult- ing services.  Focused and specialized in Data analytics  Offers different data analytics software developed by the Saracus Saracus  Speech to text solution offered for call center optimization.  Not focused on the voice market.  Startup and consulting company focused on innovation and providing voice spe- blueShep- cific solutions and consulting services. herd  The company provide expertise in the direction of voice e-commerce, Alexa skills, Voice recognition  Startup and consulting company focused on innovation and providing voice spe- cific solutions and consulting services. Bytabo  The company provide expertise in the direction of voice e-commerce, Alexa skills, Voice recognition Table 6: Voice Consulting based Partners

The second category (cf. Table 6) can be defined as voice consulting based partners. These categories include the list of companies which are start-ups as voice-based consulting and ser- vice providers. In addition, these companies have skills in voice skills API such as Google Skills Kit, Amazon Alexa Skills to develop different voice assistant specific applications. Their voice consulting strategy and competencies completely align with the demand of the current voice mar- ket. Hence, the consulting companies like axxessio can really get benefits from a partnership with these companies. For example, Consetto GmbH is a consulting firm founded in 2014 in Darm- stadt mainly focuses on Alexa and Google skill development to control public and business skills using voice. As we are intended to hit the B2B platform, we could see this company as a potential partner as they provide many Business Intelligence skills. Similarly, there are many other voice consulting companies like BlueShephard and Bytabohich can be our potential partners, but the main concern is about their existence in the market. These companies are quite new to the mar- ket. Also, their customer and partner portfolio is not established enough that can provide the reliability of their solutions. Hence, the reputation of these companies is questionable.

Consulting based competitors

The third category (cf. Table 7) can be defined as consulting based companies. Accso, Mail- bornWolff and opwoco GmbH are software and IT engineering companies. Currently, these companies are focusing on providing IT specific consulting to customers which includes idea gen- eration, project management, technology, architecture, planning, conception, and implementa- tion. Based on company profile analysis, it can be said that these companies are not targeting voice as their next market but can be a potential competitor for axxessio as their IT strategy and consulting services are quite similar to axxessio. Therefore, they can be potential competitors in current and future time.

 Accso Accelerated Solutions GmbH is focused on innovation. From 2013 to 2019 - more than 100 research and/or industry publications, speakers talk, speaker and technology introduction via video, etc. Accso  The company's profile is similar to axxessio. GmbH  Offering a wide range of Software Engineering IT Consulting Services (technol- ogy, architecture, planning, conception, and implementation).  The well-established consulting company, services, and partners’ portfolio  Not working or offering any voice solution  Could be a good example for axxessio website ;)  The well-established consulting company, services, and partners’ portfolio Maiborn-  Offering a wide range of Software Engineering IT Consulting Services (technol- Wolff ogy, architecture, planning, conception, and implementation). GmbH  They are not in the direction of the voice, However, they are in the direction of Data science and AI in developing automation in logistics  Well Established portfolio in the direction of consulting services opwoco  Has fully developed product LunaMas and appTitan GmbH  Focused on software, mobile and web development  No information that they are considering to work in the direction of the voice. Table 7: Consulting based competitors

5.4 Competitive Landscape – Market Leaders

We have performed market analysis and technical analysis on big players such as Amazon, Google, Alibaba, Apple, Xiaomi and Baidu, etc. to determine their market share and ownership from their speech and voice assistant solutions. These studies will show that voice and speech technology has a great potential market and keeps many opportunities to be unfolded in the fu- ture.

5.4.1 Leaders‘ Market Share

The statistic in Figure 27 shows smart speaker shipment worldwide from 2016 to 2018, by the vendor. In 2018, the shipment of Amazon’s Alexa and Google's smart speaker products amounted to 24.2 million and 23.4 million units respectively. In addition, it can be seen in Figure 28 that most of the major part of the global intelligent market is shared between Google and Amazon in 2017. It is expected that there will be significant growth in Amazon’s market share (from 25% to 43%) while Google’s market share will be decreased (from 62% to 34%) and others (new/existing) intelligent market solution provides will share the market (from 13% to 23%) glob- ally. These statistics prove that there is a potential demand for growth in smart speakers and intelligent assistant solution provider market.

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Amazon Google Alibaba Xiaomi Baidu Others

30

24.2 25 23.4 22

20

15 11.2 10.8 10 8.9

Shipment in millionsin Shipment 7.1 5.9 5 3.6 1 0.2 0.1 0.15 0.5 0 2016* 2017 2018

Figure 27: Global smart speaker shipment by vendor 2016-2018 (in millions)

Google Assistant Amazon Alexa Other

120.0%

100.0% 13% 23%

80.0% 62% 34% 60.0%

Market share Market 40.0% 43%

20.0% 25%

0.0% 2017 2020*

Figure 28: Global intelligent assistant market shares 2017 and 2020

5.4.2 Key Points about Leading Players

 The company is focusing on leveraging Automated Speech Recognition (ASR) into IoT applications such as smart consumer electronic devices. Nuance  It is focusing on marketing their speech technology offerings  To call centers. The company’s most promising product in this criteria includes contact center automation solution.  It is increasing its market presence by promoting its virtual assistant product Echo. The product has witnessed a positive response with more than 3 million Amazon products already in the market.  The company has also open sourced it's Amazon’s Alexa Skills Kit (ASK) to developers.  It is currently focusing on competing with Nuance Communication by open sourcing its speech recognition API to the third party developers. This is a strategic roadmap of a company to expand its ecosystem. Google  In order to market its strong presence in the voice technology space, the com- pany would allow Google Docs’ users to edit and format their documents through voice commands.  Apple’s Siri was built on Nuance technology. Since the company increased its focus on voice technology, product accuracy has increased up to 90%. Apple  The company is also focusing on leveraging its voice recognition technology in the home automation application with its product namely HomeKit.

5.4.3 Product Offering of Leading Players

 Dragon Home (For individuals) – PC Users.  Dragon Premium (For individuals) – PC, Wireless & Mobile Users Nuance  Dragon Professional Individual (For business) – PC, Wireless & Mobile Users  Dragon Legal (For individuals) – PC & Wireless Users.  Dragon for Mac – Macbook & Wireless Users  Alexa Voice Service API  Amazon Echo Amazon  Amazon Echo Dot  Amazon Tap  Google Now Google  Google Cloud Speech API  Google Home (Upcoming)  Siri Apple  Dictation & Speech (Speech to Text platform)  HomeKit (Home Automation SDK)  Cortana Microsoft  API and SDK such as Microsoft Speech API

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5.4.4 Competitive Market Share Analysis

 The top seven companies in the voice recognition market, includes Nuance Communication, Amazon.com Inc., Google Inc. Apple Inc., Microsoft Cor- poration, IBM Corp. and Baidu Inc.  These companies represent more than 51% of the market share in the software space. Nuance communication domi- nates the market accounting 11.1% share of the total voice recognition soft- ware market. Apple’s Siri was built by Nuance communication through tech- nological collaboration.  Amazon.com Inc., Google Inc., Apple Inc., and Microsoft Corporation are the other prominent players in the voice recognition mar- ket. Amazon.com, Inc. has sold a staggering 3 million Echo, a voice recognition product globally. Siri and HomeKit have helped Apple Inc. to build a competitive position in this indus- try. The aforementioned four players have open source their API to developers, which would expand their ecosystem in the near future.  Baidu, Inc. is a notable player in this market that has achieved 95% accuracy in the loud environment with its Wrap-CTC. The company has open source it to developers in 2016. Nortek, Inc. a home automation company, is expected to be an emerging player in this market with its acquisition of natural language processing platform, Nuiku, in June 2016.

5.4.5 Competitive Strategy Adopted by Leading Players

Open-sourcing the speech recognition Competing for the lucrative artificial intel- software development kit ligence market Several tech giants, including Amazon.com, Technology giants, including Apple Inc., Google Inc., and Apple Inc., have enabled free Google Inc., and Microsoft Corporation, are fo- accessibility to the voice-activation software cusing on leveraging artificial intelligence in all development kit for the developers. This will voice recognition applications. For instance, expand the applications beyond their first- IBM acquired Griffith Pair’s artificial intelli- party services. Amazon.com, Inc. open- gence technology for enriching IBM ’s sourced the machine learning engine that su- human-machine interaction capabilities as the premacies its shopping recommendations, AI technology offers a feedback loop for ma- Google Inc. open-sourced its AI framework, chines and humans to learn from and teach TensorFlow, which influences the voice- each other. Additionally, Apple Inc. acquired recognition capabilities of Android and its core VocalIQ, a UK-based company that primarily search engine. Facebook, Inc. open-sourced focuses on speech processing technology. custom hardware designs to run its latest AI The acquisition is expected to improve Siri algorithms. with VocalIQ’s advanced AI technology.

In-organic growth to strengthen the com- Moving into Virtual Space petitive position Voice recognition technology has significant Prominent players in the voice recognition opportunities in the home automation industry. market following an inorganic growth strategy

Amazon.com Inc. and Google Inc. introduced to obtain a competitive advantage in this in- their voice-based home automation products dustry. Following are a few of the acquisitions called Echo and Google Home, respectively. observed in this industry: Apple, Inc. has planned to launch an intelligent hub. The company’s intelligent hub is not ex-  In 2016, Inc. ac- pected to be an entirely new product, but ra- quired TouchCommerce ther, it would be an overhauled Apple TV. The  In 2015, Apple, Inc. acquired VocalIQ product is expected to be commercially  In 2014, Google, Inc. acquired DeepMind launched by the first quarter of 2017. Technologies  In 2013 Amazon.com, Inc. acquired IVONA Software

5.4.6 Analyst View from Leaders’ Competitive Strategy

Voice recognition software provider should Quality and cost-wise balance voice recog- provide wider support for voice across hand- nition solution must be planned as enter- sets and tablets. This would curtail frauds in- prises are compelled to keep discretionary creased security in residential as well as com- spending to a minimum, and are planning to mercial applications. Additionally, this will purchase products and services that can ex- pave a way for the emergence of autonomous hibit a quantitative return on investment. interaction between users and devices.

Open-sourcing the APIs and software de- Tapping lucrative countries of Asia Pacific velopment kit enables other developers to including India and China would help compa- customize it as per the needs and also propels nies to gain competitive advantage. Rising other developers to create applications for the adoption of smartphone and growing IoT ap- entire ecosystem. This can be a source of rev- plications through projects like “Smart Cities” enue for a company in the near future. is expected to create potential revenue oppor- tunity for the ecosystem players of this market.

5.4.7 Recommendation – Key Applications to be Targeted

 5The adoption of voice recognition technology is remarkably higher in the healthcare vertical. The escalated rate of adoption can be attributed to the manifold advantages offered by the technology, including increased clinical record accuracy, comprehensiveness, and access along with enhanced patient care.  The consumer vertical represents high growth opportunities. The ever-increasing demand for smartphones, tablets, and connected devices has paved a way for the growth of the voice recognition technology market in the consumer vertical.  The home automation vertical has recently found traction and companies are focusing on introducing a virtual personal assistant. Leading companies, such as Amazon.com, Inc., and

5 Penetration is defined as the maturity of the product segment and its application. The lower penetration rate means a higher untapped market potential for growth. Growth rate is considered as the future projected CAGR till 2024. These growth rates are comparative in nature with the overall market growth rate as being the benchmark.

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Google, have already launched their products; other players are expected to follow the suit in the near future. The ris- ing inclination toward smart building in- frastructure is presumed to incite growth in the segment. The launch of several voice-activated appliances, such as smart TVs, lights, and security camera, is remarkably emerging the industry growth prospects.

5.4.8 Short Overview of Company’s Profile

Google

Google launched Home, its domestic hardware equivalent to Echo, in the US in 2016 and ex- panded into the UK in April 2017. Google Home is currently available in Canada, Australia, France, Germany, and Japan. Home allows third parties to create Conversation Actions, which are the equivalent of Amazon’s skills. It is powered by Assistant, a voice assistant that is currently available on over 100 million devices, including the iPhone, through the Allo messaging platform [43]. As of May 2017, Allo supports French, Spanish, German, Hindi and Japanese and we expect some of these languages to expand to the Home device over time. Irrespective of the assistant interface, voice capabilities have been built into the Google Search and YouTube apps since 2009. Google’s main advantage in the voice landscape is its deep understanding of its users through search and its range of other services, such as Gmail.

Amazon

Powered by voice assistant Alexa, the Amazon Echo first went on sale in the US in 2014 exclu- sively for Amazon Prime members but became widely available in 2015. The launch of the Echo and the smaller Echo Dot at the end of September 2016 in the UK and Germany kick-started consumer interest by creating a new device category for voice. Amazon has recently launched versions of the Echo with a screen (Echo Show) and a camera (Echo Look). Alexa hosts third- party skills, which function much like apps but over a voice-user interface (VUI). They can deliver entertainment and information, execute an action, or enable control of other devices. Amazon has also made Alexa available to hardware developers as Alexa Voice Service to build into their own products in an attempt to stimulate the market. As an e-commerce platform, Amazon’s strongest advantage over its competitors in this category is its unparalleled understanding of consumer shopping.

Apple

Apple is a voice pioneer, having launched its voice assistant Siri in 2011. Late to the smart speaker category, it announced the launch of its HomePod speaker at the Apple Worldwide De- velopers Conference (WWDC) in June 2017 [44]. While it has integrated Siri into wearables such

as the Apple Watch and AirPods, it is challenged by a comparative lack of machine-learning ca- pabilities and user data to make a voice assistant fully intelligent, despite its sophisticated aes- thetic that appeals to design-conscious users. The emphasis on audio quality in the launch of the HomePod, rather than its role as a digital assistant, reflects this, as does its wider strategic focus on data privacy and security. Neverthe- less, Siri’s strength is its global reach of 36 countries and ability to speak 21 languages [45].

Microsoft

Microsoft has developed Cortana, which works across Windows platforms and will be incorpo- rated into Harman Kardon’s smart speaker in the United States in autumn 2017 [46]. Cor- tana is currently available in 13 countries, speaking English, French, Chinese (simplified), Portu- guese, German, Italian, Spanish and Japanese.

Samsung

Samsung announced in March 2017 that its voice assistant would replace S Voice in the Galaxy S8 in South Korea. Rumors point to an additional integration of , the artificial intelli- gence built by Siri’s original developers, which Samsung acquired in 2016, with the aim of building voice interfaces into all its consumer products over the coming years. Bixby previews in the United States in June 2017 [47].

Others

Chinese search giant Baidu unveiled its smart speaker Xiaoyu Zaijia (Little Fish in English) at CES in January 2017. Unlike most current devices on the market, Little Fish features a screen and camera. Chinese e-commerce platform JD.com has also launched LingLong DingDong, a home speaker that takes design cues from the Echo, in the region. Much like Echo and Home, the DingDong provides access to a suite of third-party apps or services, which must be activated before use. Although both these devices are available only in China, a consumer reach of one billion makes these products significant players.

Finally, while the Facebook Messenger digital assistant is currently text-based, it is anticipated the tech giant’s next move might be in the voice arena. Considering its user data and its machine learning skills, Facebook could be a future contender in the voice space.

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6 Use Cases for Voice

In this chapter, we are providing the list of the use case of Voice Assistant, Chat/Voice bot in different industry and application areas. We have covered use cases for industries and applica- tions such as finance/banking, retail, healthcare, logistic, automobile, etc. These use cases are followed by providing information such as benefits, beneficiaries, an example corresponding to each use cases.

Use case category: Finance/Banking Use UC1: Voice technology to provide individuals with customized, personalized banking experi- cases ences to improve their financial health and better manage their personal finances. For ex- ample: . Ask for bank account balances, pending payments or deposits . Ask insight and analysis of financial health, transaction data, and savings. . Ask about transaction history and how to reallocate extra budget UC2: Empower consumers with easily accessible insights into their investments with data- driven personalization. For example: . Inquire about their investment portfolio and how to optimize returns . Ask for stock updates and receive email/text alerts . Request to obtain market and stock performance data UC3: Voice applications for payments offer an opportunity for financial service providers to differentiate and deliver personalized banking services. For example: . Schedule and make payments to providers and credit cards . Transfer money between accounts or deposit money . Ask about transaction history dashboard with information on future or outstanding bills UC4: Offering services through Alexa Skills or Google Assistant Actions can open new doors for lenders and help to streamline the process. For example: . Ask about the latest interest rates on mortgage loans and explore refinancing options . Obtain information on small business loans and how to get access to working capital . Ask about personal loans for major expenses or debt consolidation UC5: Transition from mobile banking to voice-enabled digital customer engagement Benefits Beneficiary Examples Increase customer engagement Banks RBC [51] Leverage customer insight financial institutions USAA [52] Enable convenient banking services Consumer US Bank [53] Boost loyalty through digital channels Moneylender, Insurance Fidelity (Amazon)

Use case category: Healthcare Use UC1: A personal voice assistant to improve medication, nutrition adherence appointment re- cases minders, monitor and share wellness status, improving quality of life. For example, . Individuals with mobility disabilities or impaired vision are able to complete tasks without the need to move around. UC2: Voice-powered care assistant to enables hands-free communication patients and better workflow. UC3: Chat/ voice bot assistant to enable engaging, conversational experiences on your web- site or in your mobile app for patients, family, handicapped, etc. For example: . Reducing the number of unnecessary trips to the Doctors and saving the stress of patients. UC4: Voice assistant to reduce documentation time required in filing clinical notes, patient’s summary, medication recommendations, etc. by listening to the conversation and capturing contextual information. UC5: Efficiently running of a healthcare organization with the help of voice assistants For example, . they could capture notes automatically or priorities requests from patients remotely before attending in person.

Benefits Beneficiary Examples Improves the patient experience Senior citizens Lisa [60], LifePod [61], Re- Enable convenient patient’s services Patients minder Rosie [62], Remind- Improved doctor and patient interaction Doctors MeCare [63] Personalized patient analysis Pharmacy Senter [64], Aiva [65], Reduced repetitive documentation effort Voice and hearing bi- Merit.ai [66], Praktice.ai [67], omarkers Syllable [68], Kiroku [69], Enables hands-free communication Handicapped MDOps [70], Notable [71], Improving efficiency with voice assistants Saykara [72], Suki [74], Context analysis to make critical decisions Tenor.ai [75], Ava [76], Vo- Providing instant information to patients caliD [77], voiceitt [78], Be- Connecting Patients to Care yondVerbal [79], Cogito [80], Improve the quality of life Corti [81], Healthymize [82],

Use case category: Retail Use UC1: Voice AI based product categorization, demand forecasting, inventory planning, and re- cases plenishment. For example: . companies can prevent underperforming products from building up, stock what customers are likely to buy, achieve faster deliveries, reduce returns, and save lots of money. . identify demand for a particular product based on sales history, weather, location, promo- tions, trends and so on. UC2: Voice AI-powered pricing and inventory algorithms to define the most appropriate prices for goods and notify sellers. For example: . Best promotional offers, price optimization based on demands to acquire a customer and increase sales. UC3: Chat/Voice-based customer support to provide great customer service, help customers find items on the site, notify them about new collections, and offer them apparel similar to things they’ve already chosen. For example: . if a customer has already added black jeans to the cart, a chat/voice bot can offer them new silver Converse shoes to finish the look. . Tracking customer satisfaction and predicting/influencing customer behavior. UC4: Voice based personal assistant to estimated arrival time and current status of the deliv- ery or reorder items they’ve previously bought. For example: . ask Alexa to add carrots to add in the shopping cart. UC5: Voice based in-store assistance and cashier-free stores to assist customers in finding desired products and fast as well as hands-free billing process. Benefits Beneficiary Examples Improved and personalized customer ser- Consumer Trulia (Facebook Messen- vices and satisfaction ger), Conversational Com- Convenient product finder and styling tips. Retailer merce Via Answer Engine Improved sales and communication Transportation Optimization (AEO) [54], Styl- The unforgettable in-store shopping experi- Payment management ist Match [56], Shopping Ac- ence tions [55], Tone of Voice [57], Automation of routine shopping Chain management Voice-Controlled IoT [58], Convenience and ability to do things Voice-Activated Coupons hands-free [59], eBay, Kroger, Lalafo,

Use case category: Logistic Use UC1: Voice AI based tracking to check the location or the status of any in-transit delivery, ve- cases hicle or agent. For example: . Your truck has crossed the intersection at Kassinostraße Road and moving towards its des- tination

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UC2: Voice based enterprise system interactions and communication enable better visibility, control, and transparency across the end-to-end movement of resources. UC3: Voice-controlled automation to initiate planning of schedules and allocate deliveries and tasks to different stakeholders. UC4: Voice based automation of multiple interlinking and integrations of other systems and status tracking of the different process such as the progress, status, and reports of multiple processes, and even initiate some of these processes. UC5: Voice based automation of logistic process visibility and transparency such as reporting and notifying about traffic interaction, weather, eventual customer experience, parcel safety and speeding of delivery vehicles to managers. For example, Manager is asking for, . Please share my parcel tracking to be delivered today . Share my high-priority task Benefits Beneficiary Examples Improved customer satisfaction, interaction, Multiple stakeholders Amazon [113], ebay and communication associated with logistics Optimize time in information forwarding management: Carrier Improved quality and consistency of infor- services, 3rd party lo- mation transfer in real-time gistic partners, distribu- Reduced costs and time, and increase effi- tors, tracking and re- ciency along with profitability source services, etc.

Automation of route tracking End-user and customer Convenience and ability to do things Logistic and s hands-free to fetch the information

Use case category: Automobile Use UC1: Voice based AI to provide hands-free access to different services and applications. For cases example: . Make a phone call and send messages, ask for directions/navigation, . Start/stop playing music / playing a radio station / start playing a podcast, . Ask about movies, restaurants, order for food/beverage for pick-up, shop for products . Control smart home devices from a car. UC2: Voice based AI to remember contexts and conversations then the voice assistant can plan ahead and remind users of important issues UC3: Voice based AI assistant to adapt to many different people and their situation by know- ing not only their personal preferences but also their language and culture. For example: . Using user profile, behavioral preferences, driver history, voice biometrics for the personal- ized driving experience. . Assistant understands the emotional states of the vehicle users and can act accordingly. . The assistant to learn over time and to handle new and ambiguous situations UC4: Using voice assistant to identify the best suitable parking spot based on driver’s prefer- ences such as weather, price, time considerations, security, and distance. UC5: Voice AI assistant to assist drivers to provide analysis of car condition and keep them informed of exactly what they need and when about car Maintenance and in-car functionality. Benefits Beneficiary Examples Convenience and ability to do things Automobile industries Making Phone Calls (Hound hands-free to fetch the information [103]) Maximize the safety, productivity and 3rd party services or app Getting Directions / Naviga- enjoyment of customer journeys providers tion (MBUX [104], What3Words [107], speak.lives.purchasers [106]) Easy and faster access to different services Users or drivers Sending Text Messages and apps such as voice-based navigation, (TeenSafe [108]) etc. Better performance and driving experience Playing Music (Pandora [109], SoundHound [110])

Improved security using voice biometrics Asking for local recommen- dations (BrightLocal [111])

Use case category: Weather Use UC1: Voice based live weather feeds from different locations (Latitude/Longitude) cases UC2: Voice based AI-powered analysis of weather such as temperature, water level, wind and other sensors continuously transmitting data. UC3: Voice based weather maps generation such as precipitations, clouds, pressure, temper- ature, wind, weather station, etc. and provide recommendation/ notification/ warning/ tips. Benefits Beneficiary Examples Optimize time in information forwarding Weather service provid- AccuWeather for Google As- Improved quality and consistency of infor- ers, End-user, Agricul- sistant [96], Big Sky [97], mation transfer in real-time tural, Companies/ indus- Weatherology [98] Reduced costs and time, and increase effi- tries, Inventory manage- ciency in weather forecasting ment, selling strategies, Convenience and ability to do things and crop forecast hands-free to fetch the weather information People get warned earlier take appropriate precautions

Use case category: News/Quiz/Story Telling/Book Reader Use UC1: Voice based interactive and personalized audio news feeds to the users including a cases daily briefing, quiz and more UC2: Voice-controlled news/ storytelling/ booking reading/ quiz to enable skip stories, go back, or stop and dive further into a given topic. UC3: Voice based customizable voice of news forecaster or storyteller to make realistic deliv- ery of news. Benefits Beneficiary Examples Improved quality and consistency of infor- End-user and customer Google News [99], Profes- mation transfer in real-time sional ‘Newscaster’ for Alexa Convenience and ability to do things Bookseller, News pro- [100], New York Times [101] hands-free to fetch the information vider Better customer experience

Use case category: Kids or childcare Use UC1: A speech recognition company expert in children’s voice working on solving the problem cases of devices recognizing kids and improving their experience in gaming, education, etc. UC2: Voice based assistant for more interactive and hands-on curriculum in schools UC3: Voice based personal assistant to plan their schedules such as education and sports activities, and reminding kids to do them. UC4: Teach students to speak clearly as well as telling them stories or reading books and helping them in their homework. UC5: Parents can monitor their kids' activities. Benefits Beneficiary Examples Improved interaction and communication Kids SoapBox Labs [93] An interactive and fun way of learning Parents BBC Kids [94] Convenience and ability to do things Teachers Pretty Please Google [95] hands-free to fetch the information Personal assistant for kids School

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Use case category: Sports Industry Use UC1: Voice assistant to enhance the stadium experience for the sports fan. cases . Integrating voice assistant to bar services to order food and drinks delivered to the seats. . Voice-based interactive navigation. UC2: Voice based AI personal assistant can be used to provide an interactive overview of match review, discussions, etc. based on user’s preferences. UC3: Voice based player’s assistant to provide a ‘quantified self’ – useful statistics derived from performance measurements that allow athletes to improve their training, and therefore their performance. For example: . Training, health and activity monitoring, diet planning and scheduling, and personalized rec- ommendations. . AI can run through thousands of historical plays in mere seconds suggesting plays to coaches in real-time UC4: Integrating voice-based AI to sports app for personalized and preference based sports activity tracking and analysis, ticket planning and booking, alerts, match prediction, etc. . UC5: Voice/Chatbot based AI in sports helps teams and leagues engage with fans. . Engages with fans to answer questions or encourage interactions such as distributing tour- nament data or answering specific questions about the stadium, schedule, and more . Broadcast sports news keeping fans up-to-date on their favorite teams UC6: Use of NLG to generate automatically post-game coverage and assemble highlights and promote regional sports events where human sports broadcasters can't be physically pre- sent. UC7: Voice based AI assistants can help on-field refs review penalties, offsides, and other important game critical moments Benefits Beneficiary Examples Improved leagues and teams engagement Sports organizations/ in- Fitbit with fans. dustry Improve the quality of in-game officiating. Sport followers/fans Alexa [90][91] Convenience and ability to do things Food and drinks cafe A Rookie’s Guide to NFL [92] hands-free to fetch the information

An intelligent, responsive, personalized, Players Ask Fred and delightful experience for the sports fan Personal and easy raining coach and re- Advertisement industry MS Sportscaster, Sky sports duced effort of referees jeff bot

Use case category: Voice assistant for home Use . UC1: Voice based AI to make user residence more automated. For example: cases . Automatic light, security and surveillance, audio and video entertainment . Ask a question, check the weather, set a timer and alarm, listen to news/sports/podcasts, recipe and cooking instructions, checking traffic condition, call someone / send message, control smart home devices, making a purchase UC2: Voice based behavioral monitoring and user/family members’ preference based deci- sion making. UC3: Voice AI assistant to assist families to provide analysis of a home condition and keep them informed of exactly what they need and when about home Maintenance. Benefits Beneficiary Examples Convenience, comfort, and ability to do Families Smart speakers (Amazon things hands-free. echo, Google home, Apple HomePod) [86] [87] Better quality of life Home automation ser- Thermostats (Honeywell Wi- vice providers Fi, iDevices, Nest Learning) [88] Fast response and better home security 3rd party smart service Lighting system (Vocca, In- providers steon hub, Haiku home) [89]

Personal caretaker for families and home Entertainment system (Jibo, Kinect, Samsung smart tv) [89]

Use case category: Telecommunication Use UC: Voice based AI assistant customer service and sales solutions through a world-class cases Platform. For example . A virtual assistant to discover the issue and may send a text with a link to the relevant page on the website, suggest offers, instant mobile payment method . Automated self-service that allows the customer service organization to manage large vol- umes of customer interactions quickly, intelligently and in increasingly personalized ways . Voice/chatbot can enable the company to manage several chat sessions simultaneously as well as to deflect callers from the phone queue, reducing call-center volumes and eliminat- ing one of the most cited sources of consumer frustration with their Telco providers: long wait times. . Voice bot to understand caller or customer behavior and reinforcing promotional campaigns and converting more customer contacts into new sales. Benefits Beneficiary Examples Increase account enrollments Telecom service provid- Houndify ers Reduce operating costs and boost cus- Customers or users Nuance tomer satisfaction Create up-sell opportunities 3rd part service provid- Snips ers Improved online conversions Increase issue resolution rate and call de- flection

Use case category: Insurance Use UC1: Voice commands to insert standard boilerplate text or signatures into documents to cases save time and automate multi-step manual paper word. . Enable professionals to create documents and perform other computer tasks - all by voice, and reduce the physical strain of typing. UC2: Voice AI assistant to reduce dependencies on outsourced transcription services, or eliminate transcription bottlenecks. UC3: Voice commands to edit, share, manage and customized documentation or paperwork across multiple users or departments. UC4: Voice assistant for mobile documentation and reporting. . Empower mobile employees, field workers, lawyers, social workers, insurance adjusters, public safety officers, and other professionals to create documents or fill out form-based re- ports even when they are away from their desk Benefits Beneficiary Examples Improve documentation quality, turnaround Insurance service pro- Luic.ai and costs viders Faster and efficiently documentation Customers or users Nuance Saving of business time and money Telecommunication ser- Snips vices High customer satisfaction and involvement Amazon Echo (Liberty Mutual and Allstate) Streamline repetitive or manual processes.

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Use case category: Travel and Hospitality Use UC1: Virtual assistants, combined with live chat, can navigate mobile or desktop website us- cases ers directly to the information and resources they need and provides answers quickly and easily UC2: Proactive notifications and alerts can inform via voice, text or email to keep your travel- ers informed of changes. UC3: Voice assistant for mobile documentation and reporting. UC4: Voice based assistant and customized tutorial to help online consumers with the selec- tion and purchase of airline reservations, car rentals, hotel bookings, and other local attrac- tions. UC5: Voice automated self-service capabilities assist the customer to schedule a flight, report a lost bag, receive flight information and even get assistance in purchasing a complex ticket and reservations. UC6: Personalized and customer preference based voice assistance or chat/voice bot to au- tomate the trip-planning process. . Personalized call handling with proactive information delivery . Automated collection of trip information to reduce call time with agents Benefits Beneficiary Examples Quickly and efficiently assist travelers with Travel agencies American Airlines plans online Saving of business time and money Customers or users Southwest Airlines High customer satisfaction and improved Customer service pro- Amtrak experience viders Lower servicing and operational costs and Delta Airlines deliver a differentiating experience

7 Go to Market/Marketing

The main aim of marketing strategy is to create awareness, advertise axxessio in the targeted industries for each use case, and position ourselves in voice and speech recognition technology market. To achieve this goal, we have identified possible tools and methods for marketing.

Tools and methods Description Branding In recent years, axxessio has created a good reputation in the field of speech recognition. We can use the experience and knowledge from SVH project to do branding for speech recognition competency. The experience from the project includes:  SVH – Smart Voice Hub project (Speech Recognition System)  TÜV Voice Prototype Development  HISCORE – Biometric Authentication Solution Communication material  Basic webpage  Brochure  Flyers  White papers  Technical articles  Open source data PR  Speaker engagements - pitching to the industry & internal events  Articles: industry focus, consumer focus, news  Major cooperation: o Doing a pilot with a potential partner that has a strong PR impact. o University cooperation: research on movement patterns, pressure mats topic, and sponsor Master thesis for superpo- sition of speech and voice recognition.  Innovation: o Prototyping potential use cases o Incorporate best sensor equipment on the market, intention to collaborate with Microsoft in order to co-innovate and lev- erage their developer platform for PC related use cases.  Partnering: work with the Partnering team to identify the best op- tion for startups to collaborate with which fits with axxessio strat- egy. Fairs and exhibitions We have planned to participate in industry fairs and exhibitions. We have researched and identified possible industry fairs in the direc- tion of innovation, Artificial intelligence, Machine learning, NLP, NLP, Speech and voice recognition, etc., within Germany, EU and worldwide. Some of these industry fairs are mentioned below which we can plan to participate:  INTERSPEECH: 15th September 2019, Graz, Austria  ICNLSP 2019: 12 – 13th September 2019, Trento, Italy  SPECOM 2019: 20 - 25th August 2019, Istanbul, Turkey  ICASSP 2020: 4 – 8th May 2020, Barcelona, Spain

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 Other possible event, conferences, exhibitions, etc. are men- tioned in the document attached.

20190228_GoToMar ketStrategy_CommunicatoionPlan_Final.xlsx Table 8: Go to market/Marketing strategy

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