Hugo Celle / Tutorial: Responding to your voice Public

Tutorial: Responding to your voice

This is the finished Edge Impulse project for the tutorial 'Responding to your voice'. From here you acquire new training data, design impulses and train models.

Keyword spotting

About this project

Hello, World!

Speech icon on board

Have you ever wanted to make your own "Ok, Google" or "Alexa" keyword spotting model? Clone this project to build an embedded ML project detecting the "Hello World" keyword phrase.

You can also follow our tutorial to guide you through building your keyword spotting model, from data collection to deployment on embedded devices.

Sensor & Block Information

  • Microphone audio data (.wav files) @ 16000 Hz
  • MFCC DSP block for human voice audio
  • Neural Network Classifier with prediction outputs: "helloworld", "noise", "unknown"
noise.orig_train.SqueakyChair_5.wav.15000.wav.1ncrod92
unknown.ec989d6d_nohash_1.wav.1ncrnq4h
unknown.520b2c17_nohash_2.wav.1ncrnok3
noise.orig_train.Square_1.wav.87000.wav.1ncroces
helloworld.mauricio1.wav.1ncrr48j.s14
noise.orig_train.NeighborSpeaking_7.wav.15000.wav.1ncrodta
unknown.ace072ba_nohash_0.wav.1ncrnpfr
unknown.94de6a6a_nohash_0.wav.1ncrnkmt

Run this model

On any device

Dataset summary

Data collected
34m 22s
Sensor
audio @ 16KHz
Labels
helloworld, noise, unknown

Project info

Project ID 377443
License Apache 2.0
No. of views 42,560
No. of clones 0