2020 INTERSPEECH INTERSPEECH 2020

Independent Echo Path Modeling for Stereophonic Acoustic Echo Cancellation

Abstract

As stereophonic audio devices, such as smart speakers and cellphones, evolve to be daily essentials, stereophonic acoustic echo cancellation becomes more important for voice and audio applications. The cross-correlation between the far-end channels and the associated ambiguity in the estimated echo path transfer functions lead the misalignment and instability issues with conventional stereophonic acoustic echo cancellers (SAEC). In this paper, we propose a novel SAEC algorithm, which can better model the acoustic echo path between each loudspeaker and microphone. Specifically, filter adaptations are modeled independently by applying pre-whitening in solving the misalignment problem. Improvement in echo suppression capability is evaluated in terms of echo return loss enhancement(ERLE) and wakeup word detection accuracy.

🌉 Interdisciplinary Bridge — Machine Learning and Mathematics & Optimization
🧭 Keyword Pioneer — stereophonic acoustic echo cancellation
🐝 Cross-Pollinator — Deep Learning, Machine Learning, Mathematics & Optimization, Speech & Audio