The Vivaldi platform adds to the STM32Cube.AI to bring automatic recognition of sound events and audio analytic capabilities to your application based on STM32 target.
The Vivaldi platform enables your device to extract meaning from audio and to autonomously take important decisions based on a pretrained deep neural network.
Vivaldi implements “Machine learning on the edge”, an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed
Typical application fields:
- Physical event recognition
- Predictive maintenance
- Key word spotting
- Biometric voice authentication
- Sound event classification
Vivaldi enables “edge” devices (that is, small, cheap, and energy-saving components such as MEMS sensors and low power microcontroller from the STM32 series) to perform the full sequence:
- Audio sampling
- Feature extraction to transform audio data from a high to a low dimensional representation
- Binary or multiclass classification based on the pretrained algorithm
Vivaldi machine learning algorithms achieve high accuracy in defective state identification, key word spotting, physical event recognition, automatic defect recognition, biometric voice authentication and smart sensor calibration.
The Vivaldi platform adopts STM32Cube.AI for deep learning integration: a STMicroelectronics AI software extension for the well-known STM32CubeMX configuration and code generation tool.