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arXiv · 2305.19603

Intelligible Lip-to-Speech Synthesis with Speech Units

Jeongsoo Choi·Minsu Kim·Yong Man Ro
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Abstract

In this paper, we propose a novel Lip-to-Speech synthesis (L2S) framework, for synthesizing intelligible speech from a silent lip movement video. Specifically, to complement the insufficient supervisory signal of the previous L2S model, we propose to use quantized self-supervised speech representations, named speech units, as an additional prediction target for the L2S model. Therefore, the proposed L2S model is trained to generate multiple targets, mel-spectrogram and speech units. As the speech units are discrete while mel-spectrogram is continuous, the proposed multi-target L2S model can be trained with strong content supervision, without using text-labeled data. Moreover, to accurately convert the synthesized mel-spectrogram into a waveform, we introduce a multi-input vocoder that can generate a clear waveform even from blurry and noisy mel-spectrogram by referring to the speech units. Extensive experimental results confirm the effectiveness of the proposed method in L2S.

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Jeongsoo Choi, Minsu Kim, Yong Man Ro. 2023-05-31. Intelligible Lip-to-Speech Synthesis with Speech Units. https://arxiv.org/abs/2305.19603

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