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Build great voice apps of any complexity for any domain by learning both the how's and why's of voice development. In this book you'll see how we live in a golden age of voice technology and how advances in automatic speech recognition (ASR), natural language processing (NLP), and related technologies allow people to talk to machines and get reasonable responses. Today, anyone with computer access can build a working voice app. That democratization of the technology is great. But, while it's fairly easy to build a voice app that runs, it's still remarkably difficult to build a great one, one that users trust, that understands their natural ways of speaking and fulfills their needs, and that makes them want to return for more.
We start with an overview of how humans and machines produce and process conversational speech, explaining how they differ from each other and from other modalities. This is the background you need to understand the consequences of each design and implementation choice as we dive into the core principles of voice interface design. We walk you through many design and development techniques, including ones that some view as advanced, but that you can implement today. We use the Google development platform and Python, but our goal is to explain the reasons behind each technique such that you can take what you learn and implement it on any platform.
What You Will Learn
Who This Book Is For
Anyone curious about the real how's and why's of voice interface design and development. In particular, it's aimed at teams of developers, designers, and product owners who need a shared understanding of how to create successful voice interfaces using today's technology. We expect readers to have had some exposure to voice apps, at least as users.
Ann Thymé-Gobbel's career has focused on how people use speech and natural language to communicate with each other and with technology. After completing her PhD in cognitive science and linguistics from UC San Diego, she's held a broad set of voice-related UI/UX design roles in both large corporations and small start-ups, working with diverse teams in product development, client project engagements, and R&D. Her past work includes design, data analysis and establishing best practices at Nuance, voice design for mobile and in-home devices at Amazon Lab 126, and creating natural language conversations for multimodal healthcare apps at 22otters. Her research has covered automatic language detection, error correction, and discourse structure. She is currently Director of UI/UX Design at Loose Cannon Systems, the team bringing to market Milo, a handsfree wearable communicator. Ann never stops doing research: she collects and analyzes data at every opportunity and enjoys sharing herfindings with others, having presented and taught at conferences internationally.
Charles Jankowski has over 30 years' experience in industry and academia developing applications and algorithms for real-world users incorporating advanced speech recognition, speaker verification, and natural language technologies. He has used state-of-the-art machine learning processes and techniques for data analysis, performance optimization, and algorithm development. Charles has highly in-depth technical experience with state-of-the-art technologies, effective management of cross-functional teams for all facets of application deployment, and outstanding relationships with clients. Currently, he is Director of NLP at Brain Technologies, creating the Natural iOS application with which you can "Say it and Get it." Previously he was Director of NLP and Robotics at CloudMinds, Director of Speech and Natural Language at 22otters, Senior Speech Scientist at Performance Technology Partners, and Director of Professional Services at Nuance. He has also been an independent consultant. Charles holds S.B., S.M., and Ph.D. degrees from MIT, all in electrical engineering.
PART 1 - Voice System Foundations.- Chapter 1: Say Hello to Voice Systems.- Chapter 2: Keeping Voice in Mind.- Chapter 3: Running a Voice Implementation-and Noticing Issues.- PART 2 - Planning Voice System Interactions.- Chapter 4: Defining your Vision: Building What, How, and Why for Whom.- Chapter 5: From Discovery to UX and UI Design: Tools of the Voice-First Trade.- PART 3 - Building Voice System Interactions.- Chapter 6: Applying Human 'Rules of Dialog' to Reach Conversation Resolution.- Chapter 7: Resolving Incomplete Requests Through Disambiguation.- Chapter 8: Conveying Reassurance with Confidence and Confirmation.- Chapter 9: Helping Users Succeed Through Consistency.- Chapter 10: Creating Robust Coverage for Speech-to-Text Resolution.- Chapter 11: Reaching Understanding Through Parsing and Intent Resolution.- Chapter 12: Applying Accuracy Strategies to Avoid Misunderstandings.- Chapter 13: Choosing Strategies to Recover from Miscommunication.-Chapter 14: Using Context and Data to Create Smarter Conversations.- Chapter 15: Creating Secure Personalized Experiences.- PART 4 - Verifying and Deploying Voice System Interactions.- Chapter 16: Testing and Measuring Performance in Voice Systems.- Chapter 17: Tuning and Deploying Voice Systems.
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