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"
helloworld.mauricio3.wav.1ncrqtfe.s2
unknown.c392e01d_nohash_1.wav.1ncrnpn3
unknown.520b2c17_nohash_0.wav.1ncrnojp
noise.orig_train.VacuumCleaner_8.wav.47000.wav.1ncroe1a
unknown.a80f9f53_nohash_0.wav.1ncrnpj8
helloworld.mathijs2.wav.1ncrr8ab.s6
unknown.24a3e589_nohash_0.wav.1ncrnju0
unknown.8281a2a8_nohash_3.wav.1ncrnp0c

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 39,091
No. of clones 0