DOCSLIB.ORG

Cognitive Virtual Assistants Using Google Dialogflow Develop Complex Cognitive Bots Using the Google Dialogflow Platform

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Cognitive Virtual Assistants Using Google Dialogflow Develop Complex Cognitive Bots Using the Google Dialogflow Platform Cognitive Virtual Assistants Using Google Dialogflow Develop Complex Cognitive Bots Using the Google Dialogflow Platform Navin Sabharwal Amit Agrawal Cognitive Virtual Assistants Using Google Dialogflow Navin Sabharwal Amit Agrawal New Delhi, Delhi, India Mathura, India ISBN-13 (pbk): 978-1-4842-5740-1 ISBN-13 (electronic): 978-1-4842-5741-8 https://doi.org/10.1007/978-1-4842-5741-8 Copyright © 2020 by Navin Sabharwal, Amit Agrawal This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Managing Director, Apress Media LLC: Welmoed Spahr Acquisitions Editor: Celestin Suresh John Development Editor: Matthew Moodie Coordinating Editor: Aditee Mirashi Cover designed by eStudioCalamar Cover image designed by Freepik (www.freepik.com) Distributed to the book trade worldwide by Springer Science+Business Media New York, 233 Spring Street, 6th Floor, New York, NY 10013. Phone 1-800-SPRINGER, fax (201) 348-4505, email [email protected], or visit www.springeronline.com. Apress Media, LLC is a California LLC and the sole member (owner) is Springer Science + Business Media Finance Inc (SSBM Finance Inc). SSBM Finance Inc is a Delaware corporation. For information on translations, please e-mail [email protected], or visit http://www.apress.com/ rights-permissions. Apress titles may be purchased in bulk for academic, corporate, or promotional use. eBook versions and licenses are also available for most titles. For more information, reference our Print and eBook Bulk Sales web page at http://www.apress.com/bulk-sales. Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub via the book’s product page, located at www.apress.com/978-1-4842-5740-1. For more detailed information, please visit http://www.apress.com/source-code. Printed on acid-free paper Dedicated to the people I love and the God I trust. —Navin Sabharwal Dedicated to my family and friends. —Amit Agrawal Table of Contents About the Authors ................................................................................ix About the Technical Reviewer .............................................................xi Acknowledgments .............................................................................xiii Introduction ........................................................................................xv Chapter 1: Introduction to Cognitive Virtual Bots .................................1 Cognitive Virtual Assistants ...................................................................................2 Use Cases for Cognitive Virtual Assistants ............................................................4 Self-Service/Help Desk for IT Services ...........................................................4 Triage ...............................................................................................................5 Lead Generation ..............................................................................................5 E-commerce ....................................................................................................6 Google Ecosystem .................................................................................................6 Google AI Platform ...........................................................................................7 Products and Services .....................................................................................7 Chapter 2: Introduction to Google Dialogflow .....................................13 Example: Human-to-Human Interactions ............................................................13 Building Your First Bot Using Google Dialogflow .................................................16 Creating a Google Dialogflow Account ..........................................................16 Using the Dialogflow Agent ...........................................................................18 Defining the Intents and Entities ...................................................................20 v TABLE OF CONTENTS Defining an Action and Parameters ...............................................................40 Defining the Responses .................................................................................44 Integrating with the Built-in Bot Framework Web Demo ...............................49 Trying Your First Bot ............................................................................................51 Conclusion ..........................................................................................................54 Chapter 3: Advanced Concepts in Google Dialogflow .........................55 Input and Output Contexts ..................................................................................55 Follow-Up Intents ................................................................................................65 Handling Multiple Intents (Intent Priority) ...........................................................75 Intent Training ................................................................................................79 Conversation List ...........................................................................................79 Agent Settings .....................................................................................................84 Multilingual Chatbots ..........................................................................................94 Prebuilt Agents ....................................................................................................98 Fulfillment: Integration with the Weather API ....................................................106 Fulfillment ...................................................................................................107 Webhook Service .........................................................................................107 Open Source Weather API ............................................................................108 Conclusion ........................................................................................................117 Chapter 4: Chatbot Enrichment ........................................................119 Chatbot Personality ...........................................................................................119 Windows Server ..........................................................................................130 Linux Server ................................................................................................135 Personality JSON .........................................................................................138 Personality Intent.........................................................................................140 Sentiment Analysis ...........................................................................................143 vi TABLE OF CONTENTS Event Configuration: Chatbot Transfer ...............................................................151 Integration with Facebook Messenger ..............................................................158 Google Dialogflow’s Knowledge Base Integration .............................................170 Enable Beta Features ..................................................................................171 Create a Knowledge Base............................................................................172 Spell Correction.................................................................................................177 Conclusion ........................................................................................................181 Chapter 5: New Research in the Field of Cognitive Virtual Chatbots ................................................................................183 Current Research ..............................................................................................184 Research Acquisitions .......................................................................................185 Index .................................................................................................187 vii About the Authors Navin Sabharwal has 20+ years of industry experience and is an innovator, thought leader, patent holder, and author
Load more

Recommended publications
  • Chatbot for College Enquiry : Using Dialogflow
    INTERNATIONAL JOURNAL OF INFORMATION AND COMPUTING SCIENCE ISSN NO: 0972-1347 Chatbot For College Enquiry : Using Dialogflow S.Y.Raut #1 Ashwini Sham Misal#2 Shivani Ram Misal#3 Department of Information Department of Information Department of Information Technology Technology Technology Pravara Rural Engineering College, Pravara Rural Engineering College, Pravara Rural Engineering College, Loni- 413 736, India Loni- 413 736, India Loni- 413 736, India Email id: Email id: Email id: [email protected] [email protected] [email protected] Abstract – In the modern Era of technology, Chatbots is the next big thing in the era of conversational services. Our aim is to develop a conversational chatbot for giving the answer to college related enquiry in text as well as voice format. We are developing a android application which a chatbot by using Dialogflow is conversational agent building platform from google . Dialogflow is a natural language understanding platform that makes it easy for you to design and integrate a conversational user interface into your mobile app,web application , device , bot and so on. For security purpose we are using OTP system i.e One Time Password which is more secure than traditional password system. Keywords- Dialogflow, Chatbot , OTP, natural language , enquiry . I. INTRODUCTION A Student Information Chat Bot project is built using Dialogflow which uses artificial Intelligent and machine learning that analyzes users queries and understand users message. This System is a web application which provides answer to the college related query of the student very effectively. The student or user first enter the mobile number as a id and click on send OTP button then OTP send to respective mobile after entering OTP as a password then click on login and system verify the mobile number and student login in to the system.After that students just have to query through the bot which is used for chatting.
    [Show full text]
  • Rapid Response Virtual Agent for Financial Services
    Rapid Response Virtual Agent for Financial Services Financial services firms are adapting to rapidly changing customer inquiries and marketlandscape as a result of COVID-19. From spikes in digital channels, to loan deferment challenges for retail banks, to questions around the paycheck protection program (PPP) for commercial lenders, financial services’ customers have questions and want information. However, contact centers are overwhelmed and struggling to scale quickly to provide the quality and timely responses that customers expect. The Rapid Response Virtual Agent program enables financial services firms to quickly build and implement a customized Contact Center AI (CCAI) virtual agent to respond to frequently asked questions your customers have related to COVID-19 over chat, voice, and social channels. Rapid Response Virtual Agent Capabilities Reduce hold times and alleviate pressure on ● Provide up-to-date information on your your contact center: website through chat so customers can get immediate assistance. ● Create a customized contact center chatbot that can understand and respond ● Free your human agents to handle more to COVID-19 related questions you specify. complex cases with automated phone responses to common customer questions. Program Benefits Launch in weeks Provide 24/7 access to conversational Work with an established network of self-service telephony and system integration partners to Answer customer questions in 23 languages launch your chat and/or voice bot quickly. across chat, phone, social and messages. Most implementation support is free and Scale and connect to existing workflows without usage fees*. This can also be done by Expand the customer experience and yourself using simple documentation. operational efficiency with Contact Center AI and connect into existing workflows.
    [Show full text]
  • Verification of Declaration of Adherence | Update May 20Th, 2021
    Verification of Declaration of Adherence | Update May 20th, 2021 Declaring Company: Google LLC Verification-ID 2020LVL02SCOPE015 Date of Upgrade May 2021 Table of Contents 1 Need and Possibility to upgrade to v2.11, thus approved Code version 3 1.1 Original Verification against v2.6 3 1.2 Approval of the Code and accreditation of the Monitoring Body 3 1.3 Equality of Code requirements, anticipation of adaptions during prior assessment 3 1.4 Equality of verification procedures 3 2 Conclusion of suitable upgrade on a case-by-case decision 4 3 Validity 4 SCOPE Europe sprl Managing Director ING Belgium Rue de la Science 14 Jörn Wittmann IBAN BE14 3631 6553 4883 1040 BRUSSELS SWIFT / BIC: BBRUBEBB https://scope-europe.eu Company Register: 0671.468.741 [email protected] VAT: BE 0671.468.741 2 | 4 1 Need and Possibility to upgrade to v2.11, thus approved Code version 1.1 Original Verification against v2.6 The original Declaration of Adherence was against the European Data Protection Code of Conduct for Cloud Service Providers (‘EU Cloud CoC’)1 in its version 2.6 (‘v2.6’)2 as of March 2019. This verifica- tion has been successfully completed as indicated in the Public Verification Report following this Up- date Statement. 1.2 Approval of the Code and accreditation of the Monitoring Body The EU Cloud CoC as of December 2020 (‘v2.11’)3 has been developed against GDPR and hence provides mechanisms as required by Articles 40 and 41 GDPR4. As indicated in 1.1. the services con- cerned passed the verification process by the Monitoring Body of the EU Cloud CoC, i.e., SCOPE Eu- rope sprl/bvba5 (‘SCOPE Europe’).
    [Show full text]
  • Open Source Audio to Text Transcription
    Open Source Audio To Text Transcription Armorial Felice never seeps so importantly or piled any pedicurists inadequately. Alleviatory Harman friends very zonally while Sean remains interactive and splendid. Branchless Erny ingenerates unthinking or niggles orbicularly when Karim is peewee. Runs a local HTTP server with this documentation. Audacity is light free utility vehicle I use to clean a bad audio. Task to open audio source transcription app development and jaws versions seem wrong where you speak directly input devices built by analysts, it lets the social media files. To begin transcribing, workflows, and lie the video with abundant foot. Highlight the binge and together the buttons in the toolbar at every top crust the editing window that indicate strikethroughs or underlines exactly cross in factory original. Microsoft word document conversion, english that your best choice option of windows version of. AIMultiple is data driven. Transcribe provides handy keyboard shortcuts to brush the playback of the audio. It also offers more rich vocabulary options than Google, Audext allows editing transcripts without human interference. We form many users around a world including Egypt, speeches, increasing accuracy over time. Streaming analytics software product is. Many years ago, including encrypted dictation solution in some family of audio file but you get your life cycle of this. See how Google Cloud ranks. With an ideal moment to users to current best free material out profane or hard to taking. Google promises not open source applications increasingly popular products, text editor on audio will. Or audio source requirement of. Provides ample options to text! It is another free source program under the GNU General Public License.
    [Show full text]
  • Voice User Interface on the Web Human Computer Interaction Fulvio Corno, Luigi De Russis Academic Year 2019/2020 How to Create a VUI on the Web?
    Voice User Interface On The Web Human Computer Interaction Fulvio Corno, Luigi De Russis Academic Year 2019/2020 How to create a VUI on the Web? § Three (main) steps, typically: o Speech Recognition o Text manipulation (e.g., Natural Language Processing) o Speech Synthesis § We are going to start from a simple application to reach a quite complex scenario o by using HTML5, JS, and PHP § Reminder: we are interested in creating an interactive prototype, at the end 2 Human Computer Interaction Weather Web App A VUI for "chatting" about the weather Base implementation at https://github.com/polito-hci-2019/vui-example 3 Human Computer Interaction Speech Recognition and Synthesis § Web Speech API o currently a draft, experimental, unofficial HTML5 API (!) o https://wicg.github.io/speech-api/ § Covers both speech recognition and synthesis o different degrees of support by browsers 4 Human Computer Interaction Web Speech API: Speech Recognition § Accessed via the SpeechRecognition interface o provides the ability to recogniZe voice from an audio input o normally via the device's default speech recognition service § Generally, the interface's constructor is used to create a new SpeechRecognition object § The SpeechGrammar interface can be used to represent a particular set of grammar that your app should recogniZe o Grammar is defined using JSpeech Grammar Format (JSGF) 5 Human Computer Interaction Speech Recognition: A Minimal Example const recognition = new window.SpeechRecognition(); recognition.onresult = (event) => { const speechToText = event.results[0][0].transcript;
    [Show full text]
  • Invezta-Chatbot-Dialogflow.Pdf
    CONTENTS SNo. Chapter Page No. 1 Chatbot and Dialogflow – An Overview 2 2 What is Dialogflow 3 – 5 3 Features of Dialogflow 6 – 9 4 Benefits of Dialogflow 10 - 11 5 Conclusion 12 1 CHATBOTS AND DIALOGFLOW AN OVERVIEW As chatbots are gaining popularity day by day, the demand of chatbots development platforms is also rising. When you decide to delve into this exciting field of chatbots development, you will come across many platforms to assist you create your first chatbot application. The options are many and Dialogflow is one of them. There are a number of Conversational AI and Conversational UI development environments available, to build what we will call a chatbot. To some of these environments the barrier to entry is quite high, to other again not so much. Lower barrier of entry might attract much attention initially, but then run into impediments when scaling. Dialogflow has seemingly a very low barrier of entry if we consider cost, ease of use and accessibility. The other factor attracting users to Dialogflow is the desire to build interfaces on Google Assistant, Google Home and other Google related devices. 2 WHAT IS DIALOGFLOW Dialogflow erstwhile API.AI is Google-owned AI powered chatbot development framework which comes very handy to build a voice or text based bot. It’s a Machine Learning based natural language processor (NLP). Using Dialogflow we can provide delightful and natural conversational experiences to your customers. Dialogflow is Artificial Intelligence tool that enables the creation of applications for human-computer interaction. Application developers are given the tools to enhance their app’s interaction features for their customers through AI-powered text and voice discussions.
    [Show full text]
  • Ai and Ml Based Google Assistant for an Organization Using Google Cloud Platform and Dialogflow
    International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8 Issue-5, January 2020 Ai and Ml Based Google Assistant for an Organization using Google Cloud Platform and Dialogflow Chinnapa Reddy Kanakanti, Sabitha R. organizations and other tech industries were one of the first Abstract: Many people adopting Smart Assistant Devices such Industries to adopt new technologies. This integration has as Google Home. Now a days of solely engaging with a service grown massively, helping organizations reach a wider through a keyboard are over. The new modes of user interaction customer base enabling them to perform their conveniently are aided in part by this research will investigate how advancements in Artificial Intelligence and Machine Learning educational organizations are becoming ever more technology are being used to improve many services. In competitive with each other to adopt the newest particular, it will look at the development of google assistants as a advancements in technology to provide an improved delivery channel for information distribution. This project is aimed to service to satisfy users. The Organizations are now enabling implement an android-based chatbot to assist with Organization the use of technology so, customers can perform more tasks basic processes, using google tools such as Dialogflow that uses online using the voice based and conversational such as Natural language processing NLP, Actions on Google and Google Cloud Platform that expose artificial intelligence and Machine getting results, attendance, personal and academic Learning methods such as natural language understanding. information remotely and intelligent chatbots to increase Allowing users to interact with the google assistant using natural customer service and assist employees & users.
    [Show full text]
  • Universidade Federal De Goiás Faculdade De Informação E Comunicação Publicidade E Propaganda
    UNIVERSIDADE FEDERAL DE GOIÁS FACULDADE DE INFORMAÇÃO E COMUNICAÇÃO PUBLICIDADE E PROPAGANDA KETLEN KOMOREK DE AQUINO LARISSA JÁCOME DO CARMO VICTORIA FERREIRA ARANTES MARKETING DIGITAL: UMA JORNADA VIÁVEL PARA MICRONEGÓCIOS GOIÂNIA 2019 UNIVERSIDADE FEDERAL DE GOIÁS FACULDADE DE INFORMAÇÃO E COMUNICAÇÃO PUBLICIDADE E PROPAGANDA KETLEN KOMOREK DE AQUINO LARISSA JÁCOME DO CARMO VICTORIA FERREIRA ARANTES MARKETING DIGITAL: UMA JORNADA VIÁVEL PARA MICRONEGÓCIOS Projeto Experimental apresentado ao Curso de Publicidade e Propaganda da Faculdade de Informação e Comunicação da Universidade Federal de Goiás, para a obtenção de grau de Bacharel. Orientadora: Prof.ª. Dra. Thalita Sasse Fróes GOIÂNIA 2019 KETLEN KOMOREK DE AQUINO LARISSA JÁCOME DO CARMO VICTORIA FERREIRA ARANTES MARKETING DIGITAL: UMA JORNADA VIÁVEL PARA MICRONEGÓCIOS Projeto Experimental apresentado ao Curso de Publicidade e Propaganda da Faculdade de Informação e Comunicação da Universidade Federal de Goiás, para obtenção do grau de Bacharel. Aprovada em _________ de _______________ de _____________, pela Banca Examinadora constituída pelos seguintes professores. ___________________________________________________________________________ Prof.ª. Dra. Thalita Sasse Fróes - UFG Presidente da Banca ___________________________________________________________________________ Prof.ª. Ma. Alessandra Cristina Gomes - UFG ___________________________________________________________________________ Prof.ª. Ma. Karine do Prado Ferreira Gomes - UFG Aos meus duplos, companheiros, que ora me sabotaram de maneira inigualável e ora me levantaram de maneira imparável: obrigada. Um obrigado especial ao duplo que me faz sempre buscar pessoas para caminhar ao lado e crescermos juntos. Duplos, que continuem fazendo parte de mim. E que venham os próximos. AGRADECIMENTOS Este trabalho nasce de uma inquietude. Agradeço meus pais por me darem a oportunidade de morar e conhecer lugares tão diversos do Brasil e por terem me ensinado a levar minhas inquietudes para atitudes empreendedoras.
    [Show full text]
  • Cisco Contact Centers and Google Artificial Intelligence Subtitle Goes Here
    #CiscoLive Cisco Contact Centers and Google Artificial Intelligence Subtitle goes here Dominique Pfeffer, GOOGLE CCAI Technology Partners Lead Massimiliano Caranzano, CISCO Contact Center Product Sales Specialist Agenda • GOOGLE Contact Center AI • Innovation and priorities in Contact Centers market • An open architecture for modern Contact Centers • GoToMarket Evolution • AI to drive Contact Center efficiency: • Agent Assistance services • Cisco Virtual Agent • Conversational IVR PSO © 2020 Cisco and/or its affiliates. All rights reserved. Cisco Public 4 COL - 1317 Contact Center AI Built with Google’s human-like conversational AI Dominique Pfeffer, CCAI Technology Partners Lead Our products are how we innovate 1997 2005 2008 2012 2015 Search Maps Android Play Photos 9 Billion User Applications Search ranking Street View image Keyboard input Recommendations Photo search Speech recognition Popular times Assistant Developer mode Smart sharing 2004 2006 2008 2012 Gmail YouTube Chrome Drive 100% Smart Reply Recommendations Hack detection Quick Access Spam classification Better thumbnails Translation Data Loss Prevention Machine Learning Powered Introducing Cloud AI Cloud AI solutions ML professionals & service partners Less ML New expertise Cloud Contact Document Professional Services Organization ASL Job Discovery Center Understanding Cloud AI building blocks Language New New Vision Cloud Video Cloud Cloud Cloud Natural Cloud Cloud Cloud AutoML Cloud Speech-to- Dialogflow Cloud Text-to- Intelligence AutoML Vision Vision Language AutoML NL Translation Translation Text Enterprise Speech Cloud AI platform ML accelerators ML libraries Kaggle/datasets Cloud ML Cloud Cloud Cloud Cloud Learning Tensorflow Kubeflow Datasets More ML Engine Dataflow Dataproc TPU GPU expertise Machine & Deep Deep & Machine But you’ve had to make a tradeoff between great customer support and operational efficiency.
    [Show full text]
  • Developing a Chatbot for Customer Service to Metropolia UAS Student
    Sonja Merisalo Developing a Chatbot for Customer Service to Metropolia UAS Student Affairs Office Helsinki Metropolia University of Applied Sciences Master of Engineering Information Technology Master’s Thesis 26 September 2018 PREFACE Chatbots hit me in the face around November 2016 when a colleague of mine told me (with huge disbelief) that she had just talked with a chatbot - and thought that it was a real person! Of course, I had to try it out and it was quite impressive. The urge to find out more stayed in the back of my head and spurted out when I got into master-studies. The hardest part was how much to narrow down. At first, I thought I could actually make a real, working chatbot with Natural Language Processing (NLP) and high-level Artificial Intelligence (AI) - including all the testing with actual users, iterating, launch- ing, marketing, piloting period, collecting feedback… Yes, that would have been a doc- toral thesis. Since as usual, my goals and expectations were at least sky high. Ending up with “just” a proof of concept was not ideal for the ambitious me, but it was the only reasonable thing to do. Anyway, oh boy how much I learned about chatbots, Machine Learning, NLP, frameworks, libraries and coding. Thank you, my instructors! Erja Nikunen for jumping in and giving the most important technical instructions and also pulling my head down from the clouds, and Harri Airaksinen and Ville Jääskeläinen for all those inspiring and down-to-earth thoughts. Thank you, my persistent tech-angel Fredrik Gundersen for getting me started with the RiveScript framework and Teemu Vilkman & Ville Raassina for giving some nice tech- nical and designing hints.
    [Show full text]
  • Chatbots: History, Technology, and a Case Analysis Jay 1
    Chatbots: history, technology, and a case analysis Item Type Honor's Project Authors Jay, Benjamin Rights Attribution-NonCommercial-NoDerivatives 4.0 International Download date 27/09/2021 10:16:35 Item License http://creativecommons.org/licenses/by-nc-nd/4.0/ Link to Item http://hdl.handle.net/20.500.12648/1624 Running head: Chatbots: History, Technology, and a Case Analysis Jay 1 Chatbots: History, Technology, and a Case Analysis Benjamin Jay State University of New York at New Paltz Chatbots: History, Technology, and a Case Analysis Jay 2 Abstract This thesis examines the more than 50 year history of chatbots that led to the development of Amazon’s Alexa, Google’s Assistant, and Apple’s Siri. A chatbot, commonly known as a conversational agent, is a computer framework that can have a normal conversation with a user by using a natural language processor (Reshmi and Balakrishnan, 2018). The goal is to understand the psychological and mathematical theories that worked well throughout history, as well as those that did not, and the impact they had on the evolution of modern chatbots. This thesis incorporates these theories into a new chatbot created using Google’s chatbot AI platform called Dialogflow. By following a Coursera course titled Building Conversational Experiences with Dialogflow, this thesis creates a chatbot that can schedule tours of a school and can answer questions about the SUNY New Paltz 2020 Commencement ceremony. Creating even the most basic chatbot requires a comprehensive understanding of the underlying theories and extensive coding experience (Abdul-Kader & Woods, 2015). This thesis assumes a foundation knowledge of computer coding.
    [Show full text]
  • Development and Technical Implementation of an Interactive Drama for Smart Speakers
    Aalto University School of Science Master's Programme in Computer, Communication and Information Sciences Otso Ollikainen Development and technical implementation of an interactive drama for smart speakers Master's Thesis Espoo, July, 2020 Supervisor: Associate Professor Tom B¨ackstr¨om Advisor: Wesa Aapro Aalto University School of Science Master's Programme in Computer, Communication and ABSTRACT OF Information Sciences MASTER'S THESIS Author: Otso Ollikainen Title: Development and technical implementation of an interactive drama for smart speakers Date: July, 2020 Pages: 89 Major: Computer Science Code: SCI3042 Supervisor: Associate Professor Tom B¨ackstr¨om Advisor: Wesa Aapro Smart speakers have rapidly gained popularity in recent years, with their virtual assistants, such as Google Assistant and Alexa, becoming increasingly familiar in many a household. The capabilities of virtual assistants and smart speakers are expanded by third-party applications, such as Alexa Skills. The functionalities of the different applications range from alarm applications to interactive fiction, but proper interactive drama is few and far between, even though there is demand for interactive content. In this thesis, we will present different aspects of the development of an inter- active drama for smart speakers, focusing on the technical implementation. The implementation consists of the interactive drama "The Dead Are Speaking", cre- ated for Google Home smart speakers as a collaboration between Yle and Aalto University. We will discuss different technologies and tools used for the implemen- tation, factors of the format that affect the writing process, and the possibilities the concept brings. Our evaluation demonstrates that the current methodology and tools are adept in creating interesting and complex drama and interaction structures, and that the users enjoy interacting with such formats.
    [Show full text]