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1
Introduction
2
Welcome
3
Project Overview
4
What is Embedded Machine Learning
5
Keyword Spotting Worksheet
6
Data Collection
7
Creating Speech Recognition Project
8
Python Script
9
Data Augmentation
10
AI vs ML
11
What is deep learning
12
AI ML and deep learning
13
Questions
14
Technology Pipeline
15
Edge Impulse
16
Test Data First
Description:
Explore the world of TinyML in this comprehensive workshop on implementing machine learning on microcontrollers for speech recognition. Learn to train a neural network to recognize spoken words, convert it to a TensorFlow Lite model, and deploy it on an ARM microcontroller for real-time wake word detection. Dive into embedded machine learning concepts, data collection techniques, and the intricacies of creating a speech recognition project. Gain insights into AI, machine learning, and deep learning, while following along with hands-on exercises using Edge Impulse. Discover the potential of running neural networks on microcontrollers and their practical applications in this engaging session led by electrical and embedded engineer Shawn Hymel.

TinyML - Using Machine Learning on Microcontrollers to Recognize Speech

Hackaday
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