Cued Speech Generation Leveraging a Pre-trained Audiovisual Text-to-Speech Model

• URL: http://arxiv.org/abs/2501.04799v1
• Date: Wed, 08 Jan 2025 19:26:43 GMT
• Title: Cued Speech Generation Leveraging a Pre-trained Audiovisual Text-to-Speech Model
• Authors: Sanjana Sankar, Martin Lenglet, Gerard Bailly, Denis Beautemps, Thomas Hueber,
• Abstract summary: This paper presents a novel approach for the automatic generation of Cued Speech (ACSG) We explore transfer learning strategies by leveraging a pre-trained audiovisual autoregressive text-to-speech model (AVTacotron2) With a decoding accuracy at the phonetic level reaching approximately 77%, the results demonstrate the effectiveness of our approach.
• Score: 8.745106905496284
• License:
• Abstract: This paper presents a novel approach for the automatic generation of Cued Speech (ACSG), a visual communication system used by people with hearing impairment to better elicit the spoken language. We explore transfer learning strategies by leveraging a pre-trained audiovisual autoregressive text-to-speech model (AVTacotron2). This model is reprogrammed to infer Cued Speech (CS) hand and lip movements from text input. Experiments are conducted on two publicly available datasets, including one recorded specifically for this study. Performance is assessed using an automatic CS recognition system. With a decoding accuracy at the phonetic level reaching approximately 77%, the results demonstrate the effectiveness of our approach.

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