Real-time speech enhancement in noise for throat microphone using neural audio codec as foundation model

Fuente: arXiv
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Autori principali: Hauret, Julien, Joubaud, Thomas, Bavu, Éric
Natura: Preprint
Pubblicazione: 2025
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author Hauret, Julien
Joubaud, Thomas
Bavu, Éric
author_facet Hauret, Julien
Joubaud, Thomas
Bavu, Éric
contents We present a real-time speech enhancement demo using speech captured with a throat microphone. This demo aims to showcase the complete pipeline, from recording to deep learning-based post-processing, for speech captured in noisy environments with a body-conducted microphone. The throat microphone records skin vibrations, which naturally attenuate external noise, but this robustness comes at the cost of reduced audio bandwidth. To address this challenge, we fine-tune Kyutai's Mimi--a neural audio codec supporting real-time inference--on Vibravox, a dataset containing paired air-conducted and throat microphone recordings. We compare this enhancement strategy against state-of-the-art models and demonstrate its superior performance. The inference runs in an interactive interface that allows users to toggle enhancement, visualize spectrograms, and monitor processing latency.
format Preprint
id arxiv_https___arxiv_org_abs_2508_02974
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Real-time speech enhancement in noise for throat microphone using neural audio codec as foundation model
Hauret, Julien
Joubaud, Thomas
Bavu, Éric
Audio and Speech Processing
We present a real-time speech enhancement demo using speech captured with a throat microphone. This demo aims to showcase the complete pipeline, from recording to deep learning-based post-processing, for speech captured in noisy environments with a body-conducted microphone. The throat microphone records skin vibrations, which naturally attenuate external noise, but this robustness comes at the cost of reduced audio bandwidth. To address this challenge, we fine-tune Kyutai's Mimi--a neural audio codec supporting real-time inference--on Vibravox, a dataset containing paired air-conducted and throat microphone recordings. We compare this enhancement strategy against state-of-the-art models and demonstrate its superior performance. The inference runs in an interactive interface that allows users to toggle enhancement, visualize spectrograms, and monitor processing latency.
title Real-time speech enhancement in noise for throat microphone using neural audio codec as foundation model
topic Audio and Speech Processing
url https://arxiv.org/abs/2508.02974