Papers by Jichen Yang
Towards Zero-shot Learning for End-to-end Cross-modal Translation Models (2023.findings-emnlp)
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| Challenge: | End-to-end zero-shot speech translation model is based on a zero-shot approach, but it is less competitive because of the limited amount of data available for multiple modalities. |
| Approach: | They propose an end-to-end zero-shot speech translation model that connects two pre-trained uni-modality modules via word rotator’s distance. |
| Outcome: | The proposed model performs better than or as well as those of the CTC-based models and can be trained in an end-to-end style to avoid error propagation. |