NAIST’s Machine Translation Systems for IWSLT 2020 Conversational Speech Translation Task
Ryo Fukuda, Katsuhito Sudoh, Satoshi Nakamura · 2020
This paper describes NAIST's NMT system submitted to the IWSLT 2020 conversational speech translation task.We focus on the translation disfluent speech transcripts that include ASR errors and non-grammatical utterances.We tried a domain adaptation method by transferring the styles of out-of-domain data (United Nations Parallel Corpus) to be like in-domain data (Fisher transcripts).Our system results showed that the NMT model with domain adaptation outperformed a baseline.In addition, slight improvement by the style transfer was observed.