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1
Intro
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tinyML Talk Sponsors
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tinyML Vision Challenge
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tinyML Tutorials
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Vikrams Background
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About Knowles
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Applications of Knowles DSPs
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Knowles DSPs
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Fully Connected Networks
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Activation Functions
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MVM Library
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TensorFlow Lite Micro
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TensorFlow Lite Micro kernels
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Knowles TensorFlow Lite Converter
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TensorFlow Lite Micro Interpreter
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Formatting coefficients
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tflight converter
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tensorflow audio classifier
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mcps
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case study
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summary
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support
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QA
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Sphinx
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UC Size
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QFN Package
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Memory
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Multiple Mics
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Thank You
Description:
Explore the future of AI in audio processing with this tinyML talk by Vikram Shrivastava, Sr. Director of IoT Marketing at Knowles Corporate. Discover how dedicated audio processors at the edge are revolutionizing AI applications, offering improved user interfaces with lower latency and reduced costs. Learn about the challenges of implementing voice integration, essential requirements, and design capabilities needed for effective deployment. Gain insights into control interface integration, software stacks, algorithm development, and user space application development. Delve into topics such as fully connected networks, activation functions, TensorFlow Lite Micro, and Knowles DSPs. Understand the process of formatting coefficients, using the TensorFlow Lite Converter, and implementing audio classifiers. Explore real-world case studies and get answers to common questions about memory, multiple microphones, and package sizes in this comprehensive 52-minute presentation.

Dedicated Audio Processors at the Edge Are the Future of AI

tinyML
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