Multirate State Space Models for End-to-End Processing of Pulse Density Modulated Speech Signals
Updated
Updated · arxiv.org · Aug 28
Multirate State Space Models for End-to-End Processing of Pulse Density Modulated Speech Signals
1 articles · Updated · arxiv.org · Aug 28
Summary
Researchers have developed a new speech processing architecture using multirate state space models (SSMs) for direct end-to-end processing of pulse density modulated (PDM) speech signals.
The architecture enables training on standard PCM data while generalizing robustly to PDM data at various sampling rates, reducing computational overhead and memory requirements.
This approach could benefit low-power, always-on edge devices, such as hearing aids, by allowing efficient speech processing without retraining for each microphone mode.