Mastering Voice Interfaces: Creating Great Voice Apps for Real Users
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From the Back Cover
We live in a golden age of voice technology. Advances in automatic speech recognition (ASR), natural language processing (NLP) and other technologies have made it extremely viable for people to be talking to machines and getting reasonable answers. Platforms like Amazon Alexa and Google Home, and the associated tools, have made it so anyone can build a voice app, and this is excellent. What we have seen though is that it's fairly easy to build a voice app, but still remarkably difficult to build a great app, one that gets the user what they need, and hopefully the user comes back for more.
In Mastering Voice Interfaces we want to show you how to build great voice apps. We start with the basics of voice interfaces, and how they are different from others, then dive into basic design principles that we've learned in many years building these apps in the industry. As we cover a design principle, we'll also demonstrate how to implement it with one of the established voice platforms (Google Home), and show how, though the tools are great, you don't have to go too far to have to do some custom work to get what you really want. We'll walk through many design and development techniques that some would view as advanced, but that can make a huge difference in the quality of the app.
Readers of Mastering Voice Interfaces will come away with a very good understanding of what makes voice interfaces so special, learn the basic design principles are for building great voice apps, and how to actually implement those principles and create working apps.
What you will learn:
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.
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