Edge Impulse Inc. / Tutorial: Recognize sounds from audio

This is the finished Edge Impulse project for the tutorial 'Recognize sounds from audio'. From here you acquire new training data, design impulses and train models.

Creating your first impulse (100% complete)

Acquire data

Every Machine Learning project starts with data. You can capture data from a development board or your phone, or import data you already collected.

Design an impulse

Teach the model to interpret previously unseen data, based on historical data. Use this to categorize new data, or to find anomalies in sensor readings.

Deploy

Package the complete impulse up, from signal processing code to trained model, and deploy it on your device. This ensures that the impulse runs with low latency and without requiring a network connection.

Download block output

Title Type Size
MFE training data NPY file 2687 windows
MFE training labels NPY file 2687 windows
MFE testing data NPY file 394 windows
MFE testing labels NPY file 394 windows
NN Classifier model TensorFlow Lite (float32) 13 KB
NN Classifier model TensorFlow Lite (int8 quantized) 8 KB
NN Classifier model TensorFlow Lite (int8 quantized with float32 input and output) 9 KB
NN Classifier model TensorFlow SavedModel 24 KB

Summary

Data collected
15m 40s

Project info

Project ID 14301
Project version 4