Leveraging Spatial Cues from Cochlear Implant Microphones to Efficiently Enhance Speech Separation in Real-World Listening Scenes

arXiv (Cornell University)

Abstract

Speech separation approaches for single-channel, dry speech mixtures have significantly improved. However, real-world spatial and reverberant acoustic environments remain challenging, limiting the effectiveness of these approaches for assistive hearing devices like cochlear implants (CIs). To address this, we quantify the impact of real-world acoustic scenes on speech separation and explore how spatial cues can enhance separation quality efficiently. We analyze performance based on implicit spatial cues (inherent in the acoustic input and learned by the model) and explicit spatial cues (manually calculated spatial features added as auxiliary inputs). Our findings show that spatial cues (both implicit and explicit) improve separation for mixtures with spatially separated and nearby talkers. Furthermore, spatial cues enhance separation when spectral cues are ambiguous, such as when voices are similar. Explicit spatial cues are particularly beneficial when implicit spatial cues are weak. For instance, single CI microphone recordings provide weaker implicit spatial cues than bilateral CIs, but even single CIs benefit from explicit cues. These results emphasize the importance of training models on real-world data to improve generalizability in everyday listening scenarios. Additionally, our statistical analyses offer insights into how data properties influence model performance, supporting the development of efficient speech separation approaches for CIs and other assistive devices in real-world settings.

Authors 6

1. Feyisayo Olalere

   Radboud University Nijmegen

   Affiliation as printed

   Radboud University , The Netherlands

2. Kiki van der Heijden

   Radboud University Nijmegen · Mortimer B. Zuckerman Mind Brain Behavior Institute · Columbia University

   Affiliation as printed

   Mortimer B. Zuckerman Mind, Brain, Behavior Institute , Columbia University , USA

   Radboud University , The Netherlands

3. Christiaan H. Stronks Aachen Department of Otorhinolaryngology, Leiden University Medical Centre Leiden Institute for Brain and Cognition

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   Department of Otorhinolaryngology , Leiden University Medical Centre , The Netherlands

   Leiden Institute for Brain and Cognition , Leiden , The Netherlands

4. Jeroen Johannes Briaire Aachen Department of Otorhinolaryngology, Leiden University Medical Centre

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   Department of Otorhinolaryngology , Leiden University Medical Centre , The Netherlands

5. Johan H. M. Frijns
6. Marcel A. J. van Gerven

   Radboud University Nijmegen

   Affiliation as printed

   Radboud University , The Netherlands