SL-AUAID011501V1

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Audio scene classification using machine learning on STM32

Solution

Kit Description

This evaluation setup is based on the B-L475E-IOT01A Discovery kit with STM32L4 microcontroller running FP-AI-SENSING1 function pack software. The FP-AI-SENSING1 function pack for STM32Cube performs edge-based audio scene classification (ASC) based on outputs generated by neural networks (NN). The AI model is generated and optimized using the X-CUBE-AI extension for the STM32CubeMX tool. The ST BLE Sensor smartphone application (Android or iOS) completes the setup to manage the data collection and to display the recognized audio scene on a cell phone.

 

The ASC configuration captures audio using the on-board MP34DT05 digital MEMS microphone MEMS microphone. The Artificial Neural Network (ANN) does not require external memory, as it occupies only 18KB of RAM and 31KB of Flash. Audio samples are accumulated in a buffer and injected into the ASC preprocessing phase. The preprocessing phase extracts audio features into a spectrogram and implements Fast Fourier transforms (FFT) and filter bank applications followed by log scaling. The result is fed into the ASC convolutional neural network, which proceeds to classify the output labels as either indoor, outdoor, or in-vehicle at a rate of one per second.
 

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All Evaluation Features

    • Ready-to-use audio scene classification based on neural networks
    • Able to recognize the following environments:
    • Indoor
    • Outdoor
    • In vehicle
    • The package comes with a utility for data logging and annotations on an SD card
    • Compliant with the Bluetooth® Low Energy (BLE)