Speaking Without Sound: Multi-speaker Silent Speech Voicing with Facial Inputs Only

In this paper, we introduce a novel framework for generating multi-speaker speech without relying on any audible inputs. Our approach leverages silent electromyography (EMG) signals to capture linguistic content, while facial images are used to match with the vocal identity of the target speaker. Notably, we present a pitch-disentangled content embedding that enhances the extraction of linguistic content from EMG signals. Extensive analysis demonstrates that our method can generate multi-speaker speech without any audible inputs and confirms the effectiveness of the proposed pitch-disentanglement approach.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10890579
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
0.00

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article

Speaking Without Sound: Multi-speaker Silent Speech Voicing with Facial Inputs Only

Yoori Oh, Kyogu Lee, Jae Jun Lee
Speech and Audio Processing
article

Speaking Without Sound: Multi-speaker Silent Speech Voicing with Facial Inputs Only

Yoori Oh, Kyogu Lee, Jae Jun Lee
article en

Abstract

In this paper, we introduce a novel framework for generating multi-speaker speech without relying on any audible inputs. Our approach leverages silent electromyography (EMG) signals to capture linguistic content, while facial images are used to match with the vocal identity of the target speaker. Notably, we present a pitch-disentangled content embedding that enhances the extraction of linguistic content from EMG signals. Extensive analysis demonstrates that our method can generate multi-speaker speech without any audible inputs and confirms the effectiveness of the proposed pitch-disentanglement approach.

Seoul National University (KR)
Seoul National University
Openalex Percentile: Top 95%
Speech and Audio Processing
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