Papers by Chih-Chiang Chang
Investigating the Reordering Capability in CTC-based Non-Autoregressive End-to-End Speech Translation (2021.findings-acl)
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| Challenge: | Using connectionist temporal classification (CTC) for speech-to-text translation is counter-intuitive due to its monotonicity assumption. |
| Approach: | They propose to build a non-autoregressive speech-to-text translation model using connectionist temporal classification (CTC) their work shows transformer encoders can change the word order and points out the future research direction that needs to be explored more on non-Autoregressives speech translation. |
| Outcome: | The proposed model improves translation performance by using transformer encoders. |