NAIST Simultaneous Speech-to-Text Translation System for IWSLT 2022

Ryo Fukuda, Yuka Ko, Yasumasa Kano, Kosuke Doi, Hirotaka Tokuyama, Sakriani Sakti, Katsuhito Sudoh, Satoshi Nakamura


Abstract
This paper describes NAIST’s simultaneous speech translation systems developed for IWSLT 2022 Evaluation Campaign. We participated the speech-to-speech track for English-to-German and English-to-Japanese. Our primary submissions were end-to-end systems using adaptive segmentation policies based on Prefix Alignment.
Anthology ID:
2022.iwslt-1.25
Volume:
Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022)
Month:
May
Year:
2022
Address:
Dublin, Ireland (in-person and online)
Venues:
ACL | IWSLT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
286–292
Language:
URL:
https://aclanthology.org/2022.iwslt-1.25
DOI:
10.18653/v1/2022.iwslt-1.25
Bibkey:
Cite (ACL):
Ryo Fukuda, Yuka Ko, Yasumasa Kano, Kosuke Doi, Hirotaka Tokuyama, Sakriani Sakti, Katsuhito Sudoh, and Satoshi Nakamura. 2022. NAIST Simultaneous Speech-to-Text Translation System for IWSLT 2022. In Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022), pages 286–292, Dublin, Ireland (in-person and online). Association for Computational Linguistics.
Cite (Informal):
NAIST Simultaneous Speech-to-Text Translation System for IWSLT 2022 (Fukuda et al., IWSLT 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.iwslt-1.25.pdf
Data
MuST-C