Unsupervised Speech-text word-level alignment with Dynamic Programming (2025.findings-naacl)
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| Challenge: | Word-level alignment in speech-text pretraining models is limited by word-level annotated data . authors propose an iterative training method for USDP that reduces the dependency on scarce annotation resources. |
| Approach: | They propose an Unsupervised Speech-text word-level alignment with Dynamic Programming (USDP) this method uses Dynamic programming principles to iteratively refine temporal alignment predictions . |
| Outcome: | The proposed method significantly improves on speech-text pretraining tasks compared to existing methods. |
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