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1
Demo
2
Intro
3
What is Speech to Intent
4
Training code for reference model
5
Fluent.ai Speech commands dataset
6
Data processing and model training
7
MCU Inference code explanation
8
Testing the inference on device
9
Improvements and conclusion
Description:
Explore speech-to-intent model training and deployment on microcontrollers in this 30-minute video tutorial. Learn an efficient approach for device control using speech recognition, bypassing traditional text transcription methods. Discover techniques for training domain-specific speech-to-intent models and deploying them on resource-constrained Cortex M4F-based development boards like the Wio Terminal. Follow along as the instructor demonstrates data processing, model training, and MCU inference code implementation. Gain insights into testing the inference on-device and potential improvements for speech recognition on microcontrollers. Access additional resources, including GitHub repositories and related TinyML talks, to further enhance your understanding of speech-to-intent technology for low-power, low-footprint devices.

Speech-to-Intent on MCU: TinyML for Efficient Device Control - Lecture 6

Hardware.ai
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