Attention-based distributed speech enhancement for unconstrained microphone arrays with varying number of nodes
This addresses the challenge of handling variable microphone counts in ad-hoc arrays for applications like audio processing, but it is incremental as it builds on existing attention mechanisms.
The paper tackled speech enhancement in ad-hoc microphone arrays with varying numbers of nodes by proposing an attention-based method to prioritize relevant signals and ignore redundant or empty channels, achieving robustness to link failures.
Speech enhancement promises higher efficiency in ad-hoc microphone arrays than in constrained microphone arrays thanks to the wide spatial coverage of the devices in the acoustic scene. However, speech enhancement in ad-hoc microphone arrays still raises many challenges. In particular, the algorithms should be able to handle a variable number of microphones, as some devices in the array might appear or disappear. In this paper, we propose a solution that can efficiently process the spatial information captured by the different devices of the microphone array, while being robust to a link failure. To do this, we use an attention mechanism in order to put more weight on the relevant signals sent throughout the array and to neglect the redundant or empty channels.