Search Results for author: Toshiaki Nakazawa

Found 43 papers, 5 papers with code

Findings of the 2021 Conference on Machine Translation (WMT21)

no code implementations WMT (EMNLP) 2021 Farhad Akhbardeh, Arkady Arkhangorodsky, Magdalena Biesialska, Ondřej Bojar, Rajen Chatterjee, Vishrav Chaudhary, Marta R. Costa-Jussa, Cristina España-Bonet, Angela Fan, Christian Federmann, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Leonie Harter, Kenneth Heafield, Christopher Homan, Matthias Huck, Kwabena Amponsah-Kaakyire, Jungo Kasai, Daniel Khashabi, Kevin Knight, Tom Kocmi, Philipp Koehn, Nicholas Lourie, Christof Monz, Makoto Morishita, Masaaki Nagata, Ajay Nagesh, Toshiaki Nakazawa, Matteo Negri, Santanu Pal, Allahsera Auguste Tapo, Marco Turchi, Valentin Vydrin, Marcos Zampieri

This paper presents the results of the newstranslation task, the multilingual low-resourcetranslation for Indo-European languages, thetriangular translation task, and the automaticpost-editing task organised as part of the Con-ference on Machine Translation (WMT) 2021. In the news task, participants were asked tobuild machine translation systems for any of10 language pairs, to be evaluated on test setsconsisting mainly of news stories.

Machine Translation Translation

The University of Tokyo’s Submissions to the WAT 2020 Shared Task

no code implementations AACL (WAT) 2020 Matīss Rikters, Toshiaki Nakazawa, Ryokan Ri

The paper describes the development process of the The University of Tokyo’s NMT systems that were submitted to the WAT 2020 Document-level Business Scene Dialogue Translation sub-task.

NMT Translation

Revisiting Context Choices for Context-aware Machine Translation

no code implementations7 Sep 2021 Matīss Rikters, Toshiaki Nakazawa

One of the most popular methods for context-aware machine translation (MT) is to use separate encoders for the source sentence and context as multiple sources for one target sentence.

Machine Translation Translation

Modeling Target-side Inflection in Placeholder Translation

1 code implementation MTSummit 2021 Ryokan Ri, Toshiaki Nakazawa, Yoshimasa Tsuruoka

Placeholder translation systems enable the users to specify how a specific phrase is translated in the output sentence.

LEMMA Translation

Zero-pronoun Data Augmentation for Japanese-to-English Translation

no code implementations ACL (WAT) 2021 Ryokan Ri, Toshiaki Nakazawa, Yoshimasa Tsuruoka

For Japanese-to-English translation, zero pronouns in Japanese pose a challenge, since the model needs to infer and produce the corresponding pronoun in the target side of the English sentence.

Data Augmentation Machine Translation +1

Document-aligned Japanese-English Conversation Parallel Corpus

1 code implementation WMT (EMNLP) 2020 Matīss Rikters, Ryokan Ri, Tong Li, Toshiaki Nakazawa

Sentence-level (SL) machine translation (MT) has reached acceptable quality for many high-resourced languages, but not document-level (DL) MT, which is difficult to 1) train with little amount of DL data; and 2) evaluate, as the main methods and data sets focus on SL evaluation.

Machine Translation Translation

Designing the Business Conversation Corpus

1 code implementation WS 2019 Matīss Rikters, Ryokan Ri, Tong Li, Toshiaki Nakazawa

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.

 Ranked #1 on Machine Translation on Business Scene Dialogue JA-EN (using extra training data)

Machine Translation Translation

Evaluation Dataset for Zero Pronoun in Japanese to English Translation

no code implementations LREC 2020 Sho Shimazu, Sho Takase, Toshiaki Nakazawa, Naoaki Okazaki

Therefore, we present a hand-crafted dataset to evaluate whether translation models can resolve the zero pronoun problems in Japanese to English translations.

Machine Translation Translation

Overview of the 6th Workshop on Asian Translation

no code implementations WS 2019 Toshiaki Nakazawa, Nobushige Doi, Shohei Higashiyama, Chenchen Ding, Raj Dabre, Hideya Mino, Isao Goto, Win Pa Pa, Anoop Kunchukuttan, Yusuke Oda, Shantipriya Parida, Ond{\v{r}}ej Bojar, Sadao Kurohashi

This paper presents the results of the shared tasks from the 6th workshop on Asian translation (WAT2019) including Ja↔En, Ja↔Zh scientific paper translation subtasks, Ja↔En, Ja↔Ko, Ja↔En patent translation subtasks, Hi↔En, My↔En, Km↔En, Ta↔En mixed domain subtasks and Ru↔Ja news commentary translation task.


ASPEC: Asian Scientific Paper Excerpt Corpus

no code implementations LREC 2016 Toshiaki Nakazawa, Manabu Yaguchi, Kiyotaka Uchimoto, Masao Utiyama, Eiichiro Sumita, Sadao Kurohashi, Hitoshi Isahara

In this paper, we describe the details of the ASPEC (Asian Scientific Paper Excerpt Corpus), which is the first large-size parallel corpus of scientific paper domain.

Machine Translation Translation

Constructing a Chinese---Japanese Parallel Corpus from Wikipedia

no code implementations LREC 2014 Chenhui Chu, Toshiaki Nakazawa, Sadao Kurohashi

Using the system, we construct a Chinese―Japanese parallel corpus with more than 126k highly accurate parallel sentences from Wikipedia.

Machine Translation Translation

Bilingual Dictionary Construction with Transliteration Filtering

no code implementations LREC 2014 John Richardson, Toshiaki Nakazawa, Sadao Kurohashi

In this paper we present a bilingual transliteration lexicon of 170K Japanese-English technical terms in the scientific domain.

Translation Transliteration

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