The connections you create with your users can be made more meaningful and impactful by allowing them to use their face and voice rather than just their mouse and keyboard when using your website. By allowing users to communicate using these methods that come more naturally, you’re not only creating a more authentic and memorable experience but you’re also pulling the user deeper into your narrative.
In this course, we’ll explore what is possible with facial and speech recognition technology on the web. We’ll talk philosophically about when and why you might leverage this type of interaction style, and then dive deep into the tools and techniques that are available. We’ll walk step by step through a fully functional speech, face, and emotion recognition example and break down exactly what’s happening every step of the way.
We’ll cover broad concepts about what tools make this possible, and what role each has in the overall system. Then we’ll examine different types of strategies for accomplishing the type of analysis we want to and the pros and cons of each. We’ll review tools like Tensorflow.js, Face++, Watson, Google Speech, and more.
At the end of this class you’ll not only have a thorough understanding of the landscape of web technology for this type of interaction, but you’ll also be able to create your own experiences from start to finish.
This course is for all levels. Beginners, intermediate students, and professionals will be able to follow the step-by-step structure of the course. Parts of the course will involve writing code, so an understanding of web technology fundamentals will help.
The subtitles are automatically generated, so the quality of the captions may vary.5 sections • 16 lectures • 5 hours 10 mins
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Introduction2 lectures 13:09 Mins
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Who am I05:06 Mins
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What we’ll be learning08:03 Mins
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The landscape of AI on the web3 lectures 26:44 Mins
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Client-side and Server-side08:51 Mins
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Basics of TensorFlow06:15 Mins
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Overview of available services11:38 Mins
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Setting up the experience6 lectures 2 Hour 07 Mins
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Overview of the demo project11:43 Mins
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Setting Up Structure & Services26:08 Mins
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Building Phases 1 & 215:35 Mins
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Building & Styling the Gameplay25:20 Mins
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Adding Visual Feedback for the User26:51 Mins
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Creating the "Game Over" State21:36 Mins
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Tapping into AI4 lectures 2 Hours 13 Mins
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Connecting position data with TensorFlow24:48 Mins
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Leveraging Google Speech for Transcription33:00 Mins
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Matching Transcripts to Phrases22:56 Mins
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Reading & Displaying Emotion with Face++52:28 Mins
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Conclusion1 lectures 10:46 Mins
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Key Concepts & Next Steps10:46 Mins
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