Improving Audiovisual Speech Recognition through Synthetic Visual Data Augmentation
Audiovisual Speech Recognition (AVSR) is a multimodal approach to speech recognition that incorporates visual information from lip movements to enhance model performance. Despite its advantages, its development remains constrained by the limited availability of labeled audiovisual (AV) datasets. This work explores the use of synthetic visual data as a solution, using an audio-driven talking-head pipeline to generate lip-synchronized visual content from existing audio data. We evaluate the effectiveness of synthetic visual data both as an augmentation strategy and as a standalone training resource, applying our approach to Spanish and Catalan. Our results show that augmenting real AV data ...
| Authors | Pol Buitrago, Pol Gàlvez, Javier Hernando |
|---|---|
| Primary category | eess.AS |
| Published | 25 September 2026 |
| Last updated at source | 25 September 2026 |
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