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Muse: Multi-modal target speaker extraction with visual cues

2020-10-15 14:10:37
Zexu Pan, Ruijie Tao, Chenglin Xu, Haizhou Li

Abstract

Speaker extraction algorithm relies on a reference speech to focus its attention on a target speaker. The reference speech is typically pre-registered as a speaker embedding. We believe that temporal synchronization between speech and lip movement is a useful cue, and target speaker embedding is also equally important. Motivated by this belief, we study a novel technique to use visual cues as the reference to extract target speaker embedding, without the need of pre-registered reference speech. We propose a multi-modal speaker extraction network, named MuSE, that is conditioned only on a lip image sequence for target speaker extraction. MuSE not only improves over AV-ConvTasnet baseline in terms of SI-SDR and PESQ, but also shows superior robustness in cross-domain evaluations.

Abstract (translated)

URL

https://arxiv.org/abs/2010.07775

PDF

https://arxiv.org/pdf/2010.07775.pdf


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