Designing the Business Conversation Corpus

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Authors Matīss Rikters, Toshiaki Nakazawa, Tong Li, Ryokan Ri
Journal/Conference Name WS 2019 11
Paper Category
Paper Abstract While the progress of machine translation of written text has come far in the past several years thanks to the increasing availability of parallel corpora and corpora-based training technologies, automatic translation of spoken text and dialogues remains challenging even for modern systems. In this paper, we aim to boost the machine translation quality of conversational texts by introducing a newly constructed Japanese-English business conversation parallel corpus. A detailed analysis of the corpus is provided along with challenging examples for automatic translation. We also experiment with adding the corpus in a machine translation training scenario and show how the resulting system benefits from its use.
Date of publication 2020
Code Programming Language Unspecified
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