Design Win

Audio scene classification using machine learning on STM32



Audio scene classification (ASC) can make objects smarter and allow them to be aware of user environments. This can add new levels of functionality and user experience in wearables, safety, environmental monitoring, healthcare, and many other applications. The challenge is to simplify software development and hardware design, especially for portable or wearable devices with processing, memory, and power constraints. Our solution addresses cost and design considerations by leveraging Artificial Intelligence on cost-effective, ultra-low-power STM32 microcontrollers.

The system captures ambient sound from two MP34DT05 digital MEMS omnidirectional microphones to ensure accurate acoustic sensing and efficient processing by the STM32L475VG microcontroller. This ultra-low-power MCU features signal processing peripherals and a floating-point unit (FPU) for rapid AI software execution. The FP-AI-SENSING software configures the solution for ASC involving neural network libraries generated by the X-CUBE-AI extension for STM32CubeMX.

The STM32WB55VGY provides ultra-low-power wireless connectivity compliant with the Bluetooth® Low Energy SIG specification 5.2. The algorithm outputs can be transmitted via Bluetooth to a smartphone with suitable app, such as the ST BLE Sensor app (ver. 4.1.0 or higher) for Android and iOS devices. This app can display resulting acoustic scene classifications and inferences, as well as activate data logging on the ASC system for AI retraining purposes.

The result is a cost-effective and low-power solution for audio scene classification based on AI neural network technology. It allows users with the smartphone app to see the environment recognized (e.g., indoor, outdoor, in vehicle, etc.) from environmental audio data.

  • All Features

    • Ready-to-use firmware featuring an artificial neural network (ANN) implementation for real-time audio scene classification
    • The edge processing approach ensures lower power consumption and latencies than centralized cloud solutions, and provides greater privacy in audio (and image) based applications
    • Ultra-low power implementation based on the use of a real-time operating system (RTOS)
    • Compatible with ST BLE Sensor application for Android/iOS, to display recognized audio scenes and to manage data logging
    • Easy portability across different MCU families, thanks to STM32Cube
    • Compliant with the Bluetooth® Low Energy (BLE) SIG specification v5.2