tinyML Summit 2022: Dissecting a low power AI/ML edge application: Noise Suppression

tinyML Summit 2022
tinyML Audio Session
Dissecting a low power AI/ML edge application: Noise Suppression
Raj PAWATE, Group Director, Tensilica IPG, Cadence Design Systems Inc.

Noise suppression is an important pre-processing function that is needed to reduce cognitive loading whether you are listening to music or on a conference call in today’s work-from-home use case. These algorithms have transitioned from traditional spectral-subtraction-based algorithms to RNN-based algorithms and more recently to Transformer based algorithms with noticeable improvements in MOS (Mean-opinion-score). But these AI/ML based algorithms are computationally demanding with large model sizes running from a few hundred kilobytes to several megabytes. Deploying them in battery-powered devices such as earbuds or mobile phones is challenging. . In this talk, we discuss an example RNN-based Noise Suppression algorithm and demonstrate how some of the ML processing is offloaded from a DSP to an ML-optimized IP resulting in a significant reduction in energy. We discuss a robust software framework that enables developers to mix and choose the best of both traditional and ML-based processing functions for a pleasant user experience.

source