4 citations · 6 across the 5 of their papers we have counts for
5 papers
NAIST Simultaneous Speech Translation System for IWSLT 2024
Yuka Ko, Ryo Fukuda, Yuta Nishikawa +9
This paper describes NAIST's submission to the simultaneous track of the IWSLT 2024 Evaluation Campaign: English-to-{German, Japanese, Chinese} speech-to-text translation and Engli…
Tagged End-to-End Simultaneous Speech Translation Training using Simultaneous Interpretation Data
Yuka Ko, Ryo Fukuda, Yuta Nishikawa +3
Simultaneous speech translation (SimulST) translates partial speech inputs incrementally. Although the monotonic correspondence between input and output is preferable for smaller l…
Improving Speech Translation Accuracy and Time Efficiency with Fine-tuned wav2vec 2.0-based Speech Segmentation
Ryo Fukuda, Katsuhito Sudoh, Satoshi Nakamura
Speech translation (ST) automatically converts utterances in a source language into text in another language. Splitting continuous speech into shorter segments, known as speech seg…
NAIST-SIC-Aligned: an Aligned English-Japanese Simultaneous Interpretation Corpus
Jinming Zhao, Yuka Ko, Kosuke Doi +3
It remains a question that how simultaneous interpretation (SI) data affects simultaneous machine translation (SiMT). Research has been limited due to the lack of a large-scale tra…
Speech Segmentation Optimization using Segmented Bilingual Speech Corpus for End-to-end Speech Translation
Ryo Fukuda, Katsuhito Sudoh, Satoshi Nakamura
Speech segmentation, which splits long speech into short segments, is essential for speech translation (ST). Popular VAD tools like WebRTC VAD have generally relied on pause-based…