Papers with text-based machine translation
Generating Synthetic Speech from SpokenVocab for Speech Translation (2023.findings-eacl)
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| Challenge: | End-to-end speech-totext translation (ST) models require large amounts of data to train, but their size is considerably smaller than text-based MT data. |
| Approach: | They propose a method to convert MT data to ST data via text-to-speech systems. |
| Outcome: | The proposed method improves translation quality by an average of 1.83 BLEU score while performing equally well as TTS-generated speech in improving translation quality. |
Beyond Sentence-Level End-to-End Speech Translation: Context Helps (2021.acl-long)
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| Challenge: | Document-level contextual information has shown benefits to text-based machine translation, but whether and how it helps end-to-end speech translation is still under-studied. |
| Approach: | They propose a concatenation-based ST model with adaptive feature selection for computational efficiency. |
| Outcome: | The proposed model improves translation quality and robustness to (artificial) audio segmentation errors. |