Audio signal recordings and MLP neural network configurations for sound classification on edge devices. It provides training components for exporting models to Raspberry Pi 2 or superior hardware using USB microphone inputs.
Use Cases
- Train a sound classification model using the audio signal features for edge computing.
- Deploy a real-time audio recognition system on a Raspberry Pi using the MLP neural network.
- Process audio signals registered with a USB microphone using the provided classification method.
Strengths
- Includes audio signal data formatted for MLP (Multi-Layer Perceptron) neural network training.
- Optimized for deployment on Raspberry Pi 2 and superior hardware versions.
- Designed for real-time classification using USB microphone input streams.