Search Results for author: Makoto Morishita

Found 23 papers, 4 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 Test +1

Refactoring Programs Using Large Language Models with Few-Shot Examples

no code implementations20 Nov 2023 Atsushi Shirafuji, Yusuke Oda, Jun Suzuki, Makoto Morishita, Yutaka Watanobe

A less complex and more straightforward program is a crucial factor that enhances its maintainability and makes writing secure and bug-free programs easier.

Language Modelling Large Language Model

Chat Translation Error Detection for Assisting Cross-lingual Communications

1 code implementation2 Aug 2023 Yunmeng Li, Jun Suzuki, Makoto Morishita, Kaori Abe, Ryoko Tokuhisa, Ana Brassard, Kentaro Inui

In this paper, we describe the development of a communication support system that detects erroneous translations to facilitate crosslingual communications due to the limitations of current machine chat translation methods.


Exploring the Robustness of Large Language Models for Solving Programming Problems

no code implementations26 Jun 2023 Atsushi Shirafuji, Yutaka Watanobe, Takumi Ito, Makoto Morishita, Yuki Nakamura, Yusuke Oda, Jun Suzuki

Our experimental results show that CodeGen and Codex are sensitive to the superficial modifications of problem descriptions and significantly impact code generation performance.

Code Generation

Domain Adaptation of Machine Translation with Crowdworkers

no code implementations28 Oct 2022 Makoto Morishita, Jun Suzuki, Masaaki Nagata

With the collected parallel data, we can quickly adapt a machine translation model to the target domain.

Domain Adaptation Machine Translation +1

JParaCrawl v3.0: A Large-scale English-Japanese Parallel Corpus

no code implementations LREC 2022 Makoto Morishita, Katsuki Chousa, Jun Suzuki, Masaaki Nagata

Most current machine translation models are mainly trained with parallel corpora, and their translation accuracy largely depends on the quality and quantity of the corpora.

Machine Translation Translation

Context-aware Neural Machine Translation with Mini-batch Embedding

1 code implementation EACL 2021 Makoto Morishita, Jun Suzuki, Tomoharu Iwata, Masaaki Nagata

It is crucial to provide an inter-sentence context in Neural Machine Translation (NMT) models for higher-quality translation.

Machine Translation NMT +1

A Test Set for Discourse Translation from Japanese to English

no code implementations LREC 2020 Masaaki Nagata, Makoto Morishita

We improved the translation accuracy using context-aware neural machine translation, and the improvement mainly reflects the betterment of the translation of zero pronouns.

Machine Translation Test +1

Recovery command generation towards automatic recovery in ICT systems by Seq2Seq learning

no code implementations24 Mar 2020 Hiroki Ikeuchi, Akio Watanabe, Tsutomu Hirao, Makoto Morishita, Masaaki Nishino, Yoichi Matsuo, Keishiro Watanabe

With the increase in scale and complexity of ICT systems, their operation increasingly requires automatic recovery from failures.

JParaCrawl: A Large Scale Web-Based English-Japanese Parallel Corpus

no code implementations LREC 2020 Makoto Morishita, Jun Suzuki, Masaaki Nagata

We constructed a parallel corpus for English-Japanese, for which the amount of publicly available parallel corpora is still limited.

Machine Translation Translation

NTT Neural Machine Translation Systems at WAT 2019

no code implementations WS 2019 Makoto Morishita, Jun Suzuki, Masaaki Nagata

In this paper, we describe our systems that were submitted to the translation shared tasks at WAT 2019.

Machine Translation Translation

NTT's Neural Machine Translation Systems for WMT 2018

no code implementations WS 2018 Makoto Morishita, Jun Suzuki, Masaaki Nagata

This paper describes NTT{'}s neural machine translation systems submitted to the WMT 2018 English-German and German-English news translation tasks.

Machine Translation Re-Ranking +1

Improving Neural Machine Translation by Incorporating Hierarchical Subword Features

no code implementations COLING 2018 Makoto Morishita, Jun Suzuki, Masaaki Nagata

We hypothesize that in the NMT model, the appropriate subword units for the following three modules (layers) can differ: (1) the encoder embedding layer, (2) the decoder embedding layer, and (3) the decoder output layer.

Machine Translation NMT +1

Neural Reranking Improves Subjective Quality of Machine Translation: NAIST at WAT2015

no code implementations WS 2015 Graham Neubig, Makoto Morishita, Satoshi Nakamura

We further perform a detailed analysis of reasons for this increase, finding that the main contributions of the neural models lie in improvement of the grammatical correctness of the output, as opposed to improvements in lexical choice of content words.

Machine Translation Translation

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