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arXiv · 2509.20875

PAS-SE: Personalized Auxiliary-Sensor Speech Enhancement for Voice Pickup in Hearables

Mattes Ohlenbusch·Mikolaj Kegler·Marko Stamenovic
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Abstract

Speech enhancement for voice pickup in hearables aims to improve the user's voice by suppressing noise and interfering talkers, while maintaining own-voice quality. For single-channel methods, it is particularly challenging to distinguish the target from interfering talkers without additional context. In this paper, we compare two strategies to resolve this ambiguity: personalized speech enhancement (PSE), which uses enrollment utterances to represent the target, and auxiliary-sensor speech enhancement (AS-SE), which uses in-ear microphones as additional input. We evaluate the strategies on two public datasets, employing different auxiliary sensor arrays, to investigate their cross-dataset generalization. We propose training-time augmentations to facilitate cross-dataset generalization of AS-SE systems. We also show that combining PSE and AS-SE (PAS-SE) provides complementary performance benefits, especially when enrollment speech is recorded with the in-ear microphone. We further demonstrate that PAS-SE personalized with noisy in-ear enrollments maintains performance benefits over the AS-SE system.

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Mattes Ohlenbusch, Mikolaj Kegler, Marko Stamenovic. 2025-09-25. PAS-SE: Personalized Auxiliary-Sensor Speech Enhancement for Voice Pickup in Hearables. https://doi.org/10.1109/icassp55912.2026.11460554

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