AdaST: Dynamically Adapting Encoder States in the Decoder for End-to-End Speech-to-Text Translation

Wuwei Huang, Dexin Wang, Deyi Xiong


Anthology ID:
2021.findings-acl.224
Volume:
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Month:
August
Year:
2021
Address:
Online
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2539–2545
Language:
URL:
https://aclanthology.org/2021.findings-acl.224
DOI:
10.18653/v1/2021.findings-acl.224
Bibkey:
Cite (ACL):
Wuwei Huang, Dexin Wang, and Deyi Xiong. 2021. AdaST: Dynamically Adapting Encoder States in the Decoder for End-to-End Speech-to-Text Translation. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 2539–2545, Online. Association for Computational Linguistics.
Cite (Informal):
AdaST: Dynamically Adapting Encoder States in the Decoder for End-to-End Speech-to-Text Translation (Huang et al., Findings 2021)
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PDF:
https://aclanthology.org/2021.findings-acl.224.pdf
Video:
 https://aclanthology.org/2021.findings-acl.224.mp4