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

arXiv: https://arxiv.org/abs/2501.04799 · HTML: https://mlsanity.com/paper/2501.04799/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 24 references that are in the map.
- First posted on arXiv 8 Jan 2025.

## Builds on (most cited first, 7 of 7)

- [Deep Unsupervised Learning using Nonequilibrium Thermodynamics](https://mlsanity.com/paper/1503.03585/) (2015)
- [Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions](https://mlsanity.com/paper/1712.05884/) (2017)
- [MediaPipe: A Framework for Building Perception Pipelines](https://mlsanity.com/paper/1906.08172/) (2019)
- [Multistream neural architectures for cued-speech recognition using a pre-trained visual feature extractor and constrained CTC decoding](https://mlsanity.com/paper/2204.04965/) (2022)
- [Audiovisual Speech Synthesis using Tacotron2](https://mlsanity.com/paper/2008.00620/) (2020)
- [Bridge to Non-Barrier Communication: Gloss-Prompted Fine-grained Cued Speech Gesture Generation with Diffusion Model](https://mlsanity.com/paper/2404.19277/) (2024)
- [Investigating the dynamics of hand and lips in French Cued Speech using attention mechanisms and CTC-based decoding](https://mlsanity.com/paper/2306.08290/) (2023)

## Abstract (arXiv)

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.