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2022 ACL ACL 2022

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

Abstract

AbstractThis 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.

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning and Speech & Audio
🐣 Hot Topic Early Bird — speech-to-speech translation
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors

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

Topics

Machine Learning > Core Methods > Representation Learning Machine Learning > Application Areas > Efficient Computing Deep Learning > Learning Types > Transfer Learning Speech & Audio > Recognition > Speech Translation

Keywords

adaptive segmentation speech-to-speech translation speech translation simultaneous translation end-to-end system prefix alignment
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