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Found 43 papers, 5 papers with code
Overview of the 7th Workshop on Asian Translation
This paper presents the results of the shared tasks from the 7th workshop on Asian translation (WAT2020).
Findings of the 2021 Conference on Machine Translation (WMT21)
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.
The University of Tokyo’s Submissions to the WAT 2020 Shared Task
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.
Overview of the 9th Workshop on Asian Translation
This paper presents the results of the shared tasks from the 9th workshop on Asian translation (WAT2022).
Overview of the 8th Workshop on Asian Translation
This paper presents the results of the shared tasks from the 8th workshop on Asian translation (WAT2021).
Revisiting Context Choices for Context-aware Machine Translation
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.
Zero-pronoun Data Augmentation for Japanese-to-English Translation
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.
Document-aligned Japanese-English Conversation Parallel Corpus
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.
Findings of the 2020 Conference on Machine Translation (WMT20)
In the news task, participants were asked to build machine translation systems for any of 11 language pairs, to be evaluated on test sets consisting mainly of news stories.
Designing the Business Conversation Corpus
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)
Evaluation Dataset for Zero Pronoun in Japanese to English Translation
Therefore, we present a hand-crafted dataset to evaluate whether translation models can resolve the zero pronoun problems in Japanese to English translations.
TDDC: Timely Disclosure Documents Corpus
In this paper, we describe the details of the Timely Disclosure Documents Corpus (TDDC).
Overview of the 6th Workshop on Asian Translation
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.
Overview of the 4th Workshop on Asian Translation
For the WAT2017, 12 institutions participated in the shared tasks.
Kyoto University Participation to WAT 2017
We describe here our approaches and results on the WAT 2017 shared translation tasks.
Neural Machine Translation: Basics, Practical Aspects and Recent Trends
Machine Translation (MT) is a sub-field of NLP which has experienced a number of paradigm shifts since its inception.
Kyoto University Participation to WAT 2016
We report very good translation results, especially when using neural MT for Chinese-to-Japanese translation.
SCTB: A Chinese Treebank in Scientific Domain
Treebanks are curial for natural language processing (NLP).
Overview of the 3rd Workshop on Asian Translation
For the WAT2016, 15 institutions participated in the shared tasks.
ASPEC: Asian Scientific Paper Excerpt Corpus
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.
Simultaneous Sentence Boundary Detection and Alignment with Pivot-based Machine Translation Generated Lexicons
Sentence alignment is a task that consists in aligning the parallel sentences in a translated article pair.
Bilingual Dictionary Construction with Transliteration Filtering
In this paper we present a bilingual transliteration lexicon of 170K Japanese-English technical terms in the scientific domain.
Constructing a Chinese---Japanese Parallel Corpus from Wikipedia
Using the system, we construct a Chinese―Japanese parallel corpus with more than 126k highly accurate parallel sentences from Wikipedia.
Chinese Characters Mapping Table of Japanese, Traditional Chinese and Simplified Chinese
Chinese characters are used both in Japanese and Chinese, which are called Kanji and Hanzi respectively.
