Smart Life in a Connected World – the Future Is Now 2 | Smart Life in a Connected World – the Future Is Now Insights and Revelations
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Smart Speakers & Their Impact on Music Consumption
Everybody’s Talkin’ Smart Speakers & their impact on music consumption A special report by Music Ally for the BPI and the Entertainment Retailers Association Contents 02"Forewords 04"Executive Summary 07"Devices Guide 18"Market Data 22"The Impact on Music 34"What Comes Next? Forewords Geoff Taylor, chief executive of the BPI, and Kim Bayley, chief executive of ERA, on the potential of smart speakers for artists 1 and the music industry Forewords Kim Bayley, CEO! Geoff Taylor, CEO! Entertainment Retailers Association BPI and BRIT Awards Music began with the human voice. It is the instrument which virtually Smart speakers are poised to kickstart the next stage of the music all are born with. So how appropriate that the voice is fast emerging as streaming revolution. With fans consuming more than 100 billion the future of entertainment technology. streams of music in 2017 (audio and video), streaming has overtaken CD to become the dominant format in the music mix. The iTunes Store decoupled music buying from the disc; Spotify decoupled music access from ownership: now voice control frees music Smart speakers will undoubtedly give streaming a further boost, from the keyboard. In the process it promises music fans a more fluid attracting more casual listeners into subscription music services, as and personal relationship with the music they love. It also offers a real music is the killer app for these devices. solution to optimising streaming for the automobile. Playlists curated by streaming services are already an essential Naturally there are challenges too. The music industry has struggled to marketing channel for music, and their influence will only increase as deliver the metadata required in a digital music environment. -
Towards the Implementation of an Intelligent Software Agent for the Elderly Amir Hossein Faghih Dinevari
Towards the Implementation of an Intelligent Software Agent for the Elderly by Amir Hossein Faghih Dinevari A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science Department of Computing Science University of Alberta c Amir Hossein Faghih Dinevari, 2017 Abstract With the growing population of the elderly and the decline of population growth rate, developed countries are facing problems in taking care of their elderly. One of the issues that is becoming more severe is the issue of compan- ionship for the aged people, particularly those who chose to live independently. In order to assist the elderly, we suggest the idea of a software conversational intelligent agent as a companion and assistant. In this work, we look into the different components that are necessary for creating a personal conversational agent. We have a preliminary implementa- tion of each component. Among them, we have a personalized knowledge base which is populated by the extracted information from the conversations be- tween the user and the agent. We believe that having a personalized knowledge base helps the agent in having better, more fluent and contextual conversa- tions. We created a prototype system and conducted a preliminary evaluation to assess by users conversations of an agent with and without a personalized knowledge base. ii Table of Contents 1 Introduction 1 1.1 Motivation . 1 1.1.1 Population Trends . 1 1.1.2 Living Options for the Elderly . 2 1.1.3 Companionship . 3 1.1.4 Current Technologies . 4 1.2 Proposed System . 5 1.2.1 Personal Assistant Functionalities . -
Intellibot: a Domain-Specific Chatbot for the Insurance Industry
IntelliBot: A Domain-specific Chatbot for the Insurance Industry MOHAMMAD NURUZZAMAN A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy UNSW Canberra at Australia Defence Force Academy (ADFA) School of Business 20 October 2020 ORIGINALITY STATEMENT ‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institute, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project’s design and conception or in style, presentation and linguistic expression is acknowledged.’ Signed Date To my beloved parents Acknowledgement Writing a thesis is a great process to review not only my academic work but also the journey I took as a PhD student. I have spent four lovely years at UNSW Canberra in the Australian Defence Force Academy (ADFA). Throughout my journey in graduate school, I have been fortunate to come across so many brilliant researchers and genuine friends. It is the people who I met shaped who I am today. This thesis would not have been possible without them. My gratitude goes out to all of them. -
List of Brands
Global Consumer 2019 List of Brands Table of Contents 1. Digital music 2 2. Video-on-Demand 4 3. Video game stores 7 4. Digital video games shops 11 5. Video game streaming services 13 6. Book stores 15 7. eBook shops 19 8. Daily newspapers 22 9. Online newspapers 26 10. Magazines & weekly newspapers 30 11. Online magazines 34 12. Smartphones 38 13. Mobile carriers 39 14. Internet providers 42 15. Cable & satellite TV provider 46 16. Refrigerators 49 17. Washing machines 51 18. TVs 53 19. Speakers 55 20. Headphones 57 21. Laptops 59 22. Tablets 61 23. Desktop PC 63 24. Smart home 65 25. Smart speaker 67 26. Wearables 68 27. Fitness and health apps 70 28. Messenger services 73 29. Social networks 75 30. eCommerce 77 31. Search Engines 81 32. Online hotels & accommodation 82 33. Online flight portals 85 34. Airlines 88 35. Online package holiday portals 91 36. Online car rental provider 94 37. Online car sharing 96 38. Online ride sharing 98 39. Grocery stores 100 40. Banks 104 41. Online payment 108 42. Mobile payment 111 43. Liability insurance 114 44. Online dating services 117 45. Online event ticket provider 119 46. Food & restaurant delivery 122 47. Grocery delivery 125 48. Car Makes 129 Statista GmbH Johannes-Brahms-Platz 1 20355 Hamburg Tel. +49 40 2848 41 0 Fax +49 40 2848 41 999 [email protected] www.statista.com Steuernummer: 48/760/00518 Amtsgericht Köln: HRB 87129 Geschäftsführung: Dr. Friedrich Schwandt, Tim Kröger Commerzbank AG IBAN: DE60 2004 0000 0631 5915 00 BIC: COBADEFFXXX Umsatzsteuer-ID: DE 258551386 1. -
Iot Ecosystem Brand White Paper
IoT Ecosystem Brand White Paper The Standards and Definition of IoT Ecosystem Brand September 20th, 2020 IoT Ecosystem Brand White Paper 1 There are times when it is wise for important role in business growth Foreword corporations to take a pregnant in the years to come. Frameworks pause. To look around and see if the that encourage entrepreneurism very things that have made them and put the customer at the center successful are the right ingredients of the organisation to create lasting to secure success in the future. lifetime value right across a vibrant ecosystem. As a diligent student of corporate history and business transformation But here is the issue that has been myself it is often easy to spot, with troubling me and many others for the magic of hindsight, the point at some time. which a successful company started to fail. From then on, it's often a long, Our financial accounting models, undignified journey of management performance metrics, calculations denial and subsequent terminal of economic profit, ROCE and many David Roth decline with the destruction of much of the established metrics that shareholder value along the way. analysts plug into their spreadsheets to uncover hidden value, are all CEO The Store WPP, Corporations have a bad habit of part of an old model - a model not Chairman BrandZTM thinking they will last forever - that's designed for an ecosystem era. and BAV Group, how they are built and structured. Global They struggle to extract onto the Consumers and customers have a balance sheet the true value the very different mindset as viewed ecosystem is creating, the value to through the lens of their changing the firm, it's ecosystem partners and attitudes and bonds towards the their respective brands. -
An Analysis on the Present and Future of Chatbots
JASC: Journal of Applied Science and Computations ISSN NO: 1076-5131 An Analysis on the Present and Future of Chatbots Saveeth R1, Sowmya R2 , Varshini M2 1Assistant Professor, Department of Computer Science and Engineering, Coimbatore Institute of Technology, Coimbatore 2U.G Student, Department of Computer Science and Engineering, Coimbatore Institute of Technology, Coimbatore [email protected] [email protected], [email protected] Abstract - With the increase in messaging applications in the modern world, the evolution of chatbots, also referred to as chatter robots seem to have revolutionized not only the industrial sectors but also the lives of common people to a great extent. A chatbot is a computer program which performs all the tasks required by humans by applying Artificial Intelligence techniques like Natural Language Processing (NLP), Natural Language Understanding (NLU) and Natural Language Generation (NLG). For the chatbot to understand the query/request posted by the user, a technique called pattern-matching is employed. Structured Query Language (SQL) is used for pattern matching. The data to respond to the user request is made available through the chatbots databases. Artificial Intelligence Markup Language (AIML) [9] is used to build a bot which communicates with humans. This paper gives an overview of conversational chatbots in the new era of technological advancements. Keywords – Chatter robots, AIML, Artificial Intelligence, Pattern-matching, Neural networks I. INTRODUCTION A chatbot [1] is a conversational agent which communicates with humans to respond with the best possible result from its knowledge database. [11] The response to a particular request is made by matching the user input with the stored data in the database through pattern matching technique. -
From Eliza to Xiaoice: Challenges and Opportunities with Social Chatbots
10 Shum et al. / Front Inform Technol Electron Eng 2018 19(1):10-26 Frontiers of Information Technology & Electronic Engineering www.jzus.zju.edu.cn; engineering.cae.cn; www.springerlink.com ISSN 2095-9184 (print); ISSN 2095-9230 (online) E-mail: [email protected] Review: From Eliza to XiaoIce: challenges and opportunities with social chatbots Heung-yeung SHUM‡, Xiao-dong HE, Di LI Microsoft Corporation, Redmond, WA 98052, USA E-mail: [email protected]; [email protected]; [email protected] Received Dec. 10, 2017; Revision accepted Jan. 8, 2018; Crosschecked Jan. 8, 2018 Abstract: Conversational systems have come a long way since their inception in the 1960s. After decades of research and de- velopment, we have seen progress from Eliza and Parry in the 1960s and 1970s, to task-completion systems as in the Defense Advanced Research Projects Agency (DARPA) communicator program in the 2000s, to intelligent personal assistants such as Siri, in the 2010s, to today’s social chatbots like XiaoIce. Social chatbots’ appeal lies not only in their ability to respond to users’ diverse requests, but also in being able to establish an emotional connection with users. The latter is done by satisfying users’ need for communication, affection, as well as social belonging. To further the advancement and adoption of social chatbots, their design must focus on user engagement and take both intellectual quotient (IQ) and emotional quotient (EQ) into account. Users should want to engage with a social chatbot; as such, we define the success metric for social chatbots as conversation-turns per session (CPS). Using XiaoIce as an illustrative example, we discuss key technologies in building social chatbots from core chat to visual awareness to skills. -
Pdfs/115041 Speaking Sa Mple Task - Part 1.Ashx?La=En Kanda, T., T
Korean Journal of English Language and Linguistics, Vol 21, April 2021, pp. 375-391 DOI: 10.15738/kjell.21..202104.375 KOREAN JOURNAL OF ENGLISH LANGUAGE AND LINGUISTICS ISSN: 1598-1398 / e-ISSN 2586-7474 http://journal.kasell.or.kr Exploring the Use of An Artificial Intelligence Chatbot as Second Language Conversation Partners* Dongkwang Shin (Gwangju National University of Education) Heyoung Kim (Chung-Ang University) Jang Ho Lee (Chung-Ang University) Hyejin Yang (Chung-Ang University) ABSTRACT This is an open-access article Shin, Dongkwang, Heyoung Kim, Jang Ho Lee and Hyejin Yang. 2021. distributed under the terms of the Exploring the use of an artificial intelligence chatbot as second language Creative Commons License, which conversation partners. Korean Journal of English Language and Linguistics permits unrestricted non-commercial 21, 375-391. use, distribution, and reproduction in any medium, provided the This study investigated the appropriateness of using artificially intelligent original work is properly cited. chatbots as conversation partners for second language (L2) learners. 27 Korean high school and 26 college students had a task-oriented conversation Received: March 23, 2021 with a text-based chatbot, Mitsuku, for 20 minutes. Chat log data were Revised: April 20, 2021 collected and analyzed quantitatively and qualitatively in terms of the Accepted: April 25, 2021 quantity of students’ utterances and their vocabulary levels, along with the Dongkwang Shin (1st author) degree of conversation task success between the chatbot and its users. Both Professor, Gwangju National groups finished their tasks, successfully developing conversations with the Univ. of Education chatbot and producing double the expected minimum quantity of utterances, [email protected] although their performances varied individually. -
Smart Digital Assistant Industry Analysis
Snippets: Smart Digital Assistant Industry Analysis November 2019 These are the snippets from our report on Smart Digital Assistant Industry Analysis and Opportunities for Technology Service Providers (TSP) CLICK HERE To access the full report 1 Source : DRAUP 1 Draup empowers sales teams with comprehensive industry, account & stakeholder intelligence to enable microtargeting 2 www.draup.com Source : DRAUP 2 AGENDA 01 Smart Digital Market Overview ➢ This section provides an overview of : 02 Smart Digital Assistant Segmentation ❑ Market Overview 03 Smart Digital Assistant Footprint ❑ Market Trends ❑ Smart Digital Assistant Use Cases 04 Smart Digital Assistant - End User Industry ❑ Key comparison of market capabilities across Top Players 05 Focus Areas & Key Services Opportunities Topics covered in the Snippets Report Topics covered only in the Full Report Send your requests to [email protected] to receive the Full Report 33 Source: Draup Overview: Increasing smart homes, usage of smartphones coupled with growing demand for home assistance and automation in customer service sectors are projected to drive the demand for Virtual Assistant Key Findings 25 ❖ North America held a substantial share of the global intelligent virtual assistant market in 2018, due to the increasing adoption of smart home 20 technology. 15 10 ❖ Pervasive computing (Internet of Things) is emerging these days, which is creating the new opportunity for M2M (machine to machine ) and 5 M2H (machine to human) interaction, thus enabling positive growth opportunities for virtual personal assistants market in the forthcoming 0 period 2018 2025 ❖ Text to speech technology emerged as the largest segment in 2018 and is estimated to generate revenue over USD 14.37 billion by 2025. -
Auswirkungen Von Big Data Auf Den Markt Der Onlinemedien
AUSWIRKUNGEN VON BIG DATA AUF DEN MARKT DER ONLINE MEDIEN IM RAHMEN DES ABIDA - FORSCHUNGSPROJEKTES D E S B M B F FÖRDERKENNZEICHEN 01 | S 1 5 0 1 6 A ‐ F 01IS15016A- F Goldmedia GmbH Strategy Consulting Autoren: Prof. Dr. Klaus Goldhammer, Dr. André Wiegand, Tim Prien M.A., Ina Wylenga M.A. Unter Mitarbeit von: Franziska Busse, Sophie Seyffert und Andrea Hamm Oranienburger Str. 27, 10117 Berlin-Mitte, Germany Tel. +49 30-246 266-0, Fax +49 30-246 266-66 [email protected] Datum: 28.02.2018 ABIDA - ASSESSING BIG DATA PROJEKTLAUFZEIT 01.0 3 . 2 0 1 5 - 2 8 . 0 2 . 2 0 1 9 FÖRDERKENNZEICHEN 01 | S 1 5 0 1 6 A ‐ F Westfälische Wilhelms-Universität Münster, Institut für Informations-, Telekommunikations- und Medienrecht (ITM), Zivilrechtliche Abteilung Karlsruher Institut für Technologie, Institut für Technikfolgenabschätzung und Systemanalyse (ITAS) Leibniz Universität Hannover Institut für Rechtsinformatik (IRI) Technische Universität Dortmund, Wirtschafts- und Sozialwissenschaftliche Fakultät (WiSo) Techniksoziologie Ludwig-Maximilians-Universität München, Forschungsstelle für Information, Organisation und Management (IOM) Wissenschaftszentrum Berlin für Sozialforschung www.abida.de ABIDA - Assessing Big Data Über das Gutachten Das Gutachten wurde im Rahmen des ABIDA-Projekts mit Mitteln des Bundesministeriums für Bildung und Forschung erstellt. Der Inhalt des Gutachtens gibt ausschließlich die Auffassungen der Autoren wieder. Diese decken sich nicht automatisch mit denen des Ministeriums und/oder der einzelnen Projektpartner. ABIDA lotet -
Because Sustainability
Change Making Simplified Addressing technology- business transformation in the COVID-era Contents Foreword 03 Thriving on Data 36 Applying TechnoVision 73 Leveraging data and algorithms as an asset to Introduction 04 increase the "Corporate IQ". A Few More Things 84 TechnoVision and COVID-19 06 Process on the Fly 43 TechnoVision 2020 Team 88 Building, managing, and running processes that Simplify 11 match the dynamics of the digital outside world. About Capgemini 90 You Experience 50 Being Architects of Positive Futures 15 Creating seamless user experiences for decisive, Overview of TechnoVision 18 magical moments. We Collaborate 57 Invisible Infostructure 22 Tapping into the power of the connected and Evolving the IT Infrastructure into the simple, collaborative "everything". pluggable utility it was always supposed to be. Design for Digital 64 Applications Unleashed 29 Overarching design principles to be followed and Liberating the legacy application landscape and checked throughout the journey of becoming a unleashing the next generation of powerful, agile, Technology Business. cloud-based apps. Invisible Infostructure Applications Unleashed Thriving on Data Process on the Fly You Experience We Collaborate Design for Digital Applying TechnoVision Special Foreword Patrick Nicolet Group Executive Board Member and Group CTO “Future Thinking, Change Making” businesses to operate, retailers to sell and companies to deliver. While The theme of this edition is ‘Simplify’ because, in a world where data the value of traditional ‘safe’ commodities has dropped exponentially, seems to overwhelm us all, we recognize that technology should It’s a sobering thought that, only a few months ago, when we were the popularity of technology and technological companies has soared aim to make the lives of consumers, colleagues and citizens easier. -
Autoencoder-Based Semi-Supervised Curriculum Learning for Out-Of-Domain Speaker Verification
Autoencoder-based Semi-Supervised Curriculum Learning For Out-of-domain Speaker Verification Siqi Zheng, Gang Liu, Hongbin Suo, Yun Lei Machine Intelligence Technology, Alibaba Group fzsq174630, g.liu, gaia.shb, [email protected] Abstract update its training corpus and model parameters at run-time is appealing. This study aims to improve the performance of speaker veri- fication system when no labeled out-of-domain data is avail- Curriculum learning is first formalized by Bengio et al. and able. An autoencoder-based semi-supervised curriculum learn- refers to the concept where machines start by learning simple ing scheme is proposed to automatically cluster unlabeled data structures and gradually improve to learn more complex ones and iteratively update the corpus during training. This new [2]. Bengio et al. show that this “start-small-and-gradually- training scheme allows us to (1) progressively expand the size increase-the-difficulty” strategy helps lead to faster convergence of training corpus by utilizing unlabeled data and correcting and find better local minima of non-convex problems. previous labels at run-time; and (2) improve robustness when Motivated by this idea, Ranjan et al. proposed a curricu- generalizing to multiple conditions, such as out-of-domain and lum learning based i-Vector PLDA approach to improve robust- text-independent speaker verification tasks. It is also discovered ness on noisy data [3]. Training data are split into subsets and that a denoising autoencoder can significantly enhance the clus- gradually included into the PLDA training procedure based on tering accuracy when it is trained on carefully-selected subset their difficulties.