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NAIST Simultaneous Speech-to-speech Translation System forIWSLT 2023

Ryo Fukuda,Yuta Nishikawa,Yasumasa Kano,Yuka Ko,Tomoya Yanagita,Kosuke Doi,Mana Makinae,Sakriani Sakti,Katsuhito Sudoh,Satoshi Nakamura


Abstract
This paper describes NAIST’s submission to the IWSLT 2023 Simultaneous Speech Translation task: English-to-German, Japanese, Chinese speech-to-text translation and English-to-Japanese speech-to-speech translation. Our speech-to-text system uses an end-to-end multilingual speech translation model based on large-scale pre-trained speech and text models. We add Inter-connections into the model to incorporate the outputs from intermediate layers of the pre-trained speech model and augment prefix-to-prefix text data using Bilingual Prefix Alignment to enhance the simultaneity of the offline speech translation model. Our speech-to-speech system employs an incremental text-to-speech module that consists of a Japanese pronunciation estimation model, an acoustic model, and a neural vocoder.
Anthology ID:
2023.iwslt-1.31
Volume:
Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)
Month:
July
Year:
2023
Address:
Toronto, Canada (in-person and online)
Editors:
Elizabeth Salesky,Marcello Federico,Marine Carpuat
Venue:
IWSLT
SIG:
SIGSLT
Publisher:
Association for Computational Linguistics
Note:
Pages:
330–340
Language:
URL:
https://aclanthology.org/2023.iwslt-1.31/
DOI:
10.18653/v1/2023.iwslt-1.31
Bibkey:
Cite (ACL):
Ryo Fukuda, Yuta Nishikawa, Yasumasa Kano, Yuka Ko, Tomoya Yanagita, Kosuke Doi, Mana Makinae, Sakriani Sakti, Katsuhito Sudoh, and Satoshi Nakamura. 2023.NAIST Simultaneous Speech-to-speech Translation System for IWSLT 2023. InProceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023), pages 330–340, Toronto, Canada (in-person and online). Association for Computational Linguistics.
Cite (Informal):
NAIST Simultaneous Speech-to-speech Translation System for IWSLT 2023 (Fukuda et al., IWSLT 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.iwslt-1.31.pdf


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