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WAT 2020

The 7th Workshop on Asian Translation


December 4th, 2020
Suzhou, China (Online)
(Hosted by the AACL-IJCNLP 2020)

[SPONSOR] | [TIMETABLE] | [IMPORTANT DATES] | [POLICY] | [RESEARCH PAPER] | [TRANSLATION TASK] | [EVALUATION] | [BASELINE SYSTEM] | [PAPER SUBMISSION INFORMATION] | [REGISTRATION] | [CONTACT] | [RELATED LINK] | [PREVIOUS WORKSHOPS]

INTRODUCTION

Many Asian countries are rapidly growing these days and the importance of communicating and exchanging the information with these countries has intensified. To satisfy the demand for communication among these countries, machine translation technology is essential.

Machine translation technology has rapidly evolved recently and it is seeing practical use especially between European languages. However, the translation quality of Asian languages is not that high compared to that of European languages, and machine translation technology for these languages has not reached a stage of proliferation yet. This is not only due to the lack of the language resources for Asian languages but also due to the lack of techniques to correctly transfer the meaning of sentences from/to Asian languages. Consequently, a place for gathering and sharing the resources and knowledge about Asian language translation is necessary to enhance machine translation research for Asian languages.

The Workshop on Machine Translation (WMT), the world's largest machine translation workshop, mainly targets on European languages and does not include Asian languages. The International Workshop on Spoken Language Translation (IWSLT) has spoken language translation tasks for some Asian languages using TED talk data, but these is no task for written language.

The Workshop on Asian Translation (WAT) is an open machine translation evaluation campaign focusing on Asian languages. WAT gathers and shares the resources and knowledge of Asian language translation to understand the problems to be solved for the practical use of machine translation technologies among all Asian countries. WAT is unique in that it is an "open innovation platform": the test data is fixed and open, so participants can repeat evaluations on the same data and confirm changes in translation accuracy over time. WAT has no deadline for the automatic translation quality evaluation (continuous evaluation), so participants can submit translation results at any time.

In addition to the shared tasks, the workshop will also feature scientific papers on topics related to the machine translation, especially for Asian languages. Topics of interest include, but are not limited to:

SPONSOR

AAMT
SunFlare Co., Ltd.

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IMPORTANT DATES

Translation Task Submission DeadlineSeptember 18, 2020 (EXTENDED!!)
Research Paper Submission DeadlineSeptember 18, 2020
System Description Paper Submission DeadlineOctober 23, 2020
Notification of Acceptance for Research PapersOctober 23, 2020
Review Feedback of System Description PapersOctober 30, 2020
Camera-ready Deadline (both Research and System Description Papers)November 6, 2020
Workshop DatesDecember 4, 2020 Workshop Dates

TIMETABLE

Time zone: UTC+8
10:00 - 10:05Welcome
10:05 - 11:05Research Paper I
10:05 - 10:25 : An Effective Optimization Method for Neural Machine Translation: The Case of English-Persian Bilingually Low-Resource Scenario
Benyamin Ahmadnia and Bonnie Dorr
10:25 - 10:45 : Transformer-based Double-token Bidirectional Autoregressive Decoding in Neural Machine Translation
Kenji Imamura and Eiichiro Sumita
10:45 - 11:05 : Translation of New Named Entities from English to Chinese
Zizheng Zhang, Tosho Hirasawa, Wei Houjing, Masahiro Kaneko and Mamoru Komachi
11:05 - 11:10Short Break
11:10 - 12:00Shared Task I - ASPEC / JIJI / Multimodal En-Ja
11:10 - 11:24 : Task Descriptions and Results
Toshiaki Nakazawa, Isao Goto and Hideki Nakayama
11:24 - 11:36 : Meta Ensemble for Japanese-Chinese Neural Machine Translation: Kyoto-U+ECNU Participation to WAT 2020
Zhuoyuan Mao, Yibin Shen, Chenhui Chu, Sadao Kurohashi and Cheqing Jin
11:36 - 11:48 : Neural Machine Translation Using Extracted Context based on Deep Analysis for the Japanese-English Newswire Task at WAT 2020
Isao Goto, Hideya Mino, Hitoshi Ito, Kazutaka Kinugawa, Ichiro Yamada and Hideki Tanaka
11:48 - 12:00 : TMU Japanese-English Multimodal Machine Translation System for WAT 2020
Hiroto Tamura, Tosho Hirasawa, Masahiro Kaneko and Mamoru Komachi
12:00 - 14:00Lunch Break
14:00 - 15:39Shared Task II - Indic Multilingual / UFAL EnOdia / Multimodal En-Hi / Hinden
14:00 - 14:15 : Task Descriptions and Results
Raj Dabre and Shantipriya Parida
14:15 - 14:27 : HW-TSC's Participation in the WAT 2020 Indic Languages Multilingual Task
Zhengzhe Yu, Zhanglin Wu, Xiaoyu Chen, Daimeng Wei, Hengchao Shang, Jiaxin Guo, Zongyao Li, Minghan Wang, Liangyou Li, Lizhi Lei, Hao Yang and Ying Qin
14:27 - 14:39 : NICT's Submission To WAT 2020: How Effective Are Simple Many-To-Many Neural Machine Translation Models?
Raj Dabre and Abhisek Chakrabarty
14:39 - 14:51 : ODIANLP's Participation in WAT2020
Shantipriya Parida, Petr Motlicek, Amulya Ratna Dash, Satya Ranjan Dash, Debasish Kumar Mallick, Satya Prakash Biswal, Priyanka Pattnaik, Biranchi Narayan Nayak and Ondřej Bojar
14:51 - 15:03 : Multimodal Neural Machine Translation for English to Hindi
Sahinur Rahman Laskar, Abdullah Faiz Ur Rahman Khilji, Partha Pakray and Sivaji Bandyopadhyay
15:03 - 15:15 : The ADAPT Centre's Participation in WAT 2020 English-to-Odia Translation Task
Prashanth Nayak, Rejwanul Haque and Andy Way
15:15 - 15:27 : NLPRL Odia-English: Indic Language Neural Machine Translation System
Rupjyoti Baruah and Rajesh Kumar Mundotiya
15:27 - 15:39 : WT: Wipro AI Submissions to the WAT 2020
Santanu Pal
15:39 - 15:45Short Break
15:45 - 16:55Shared Task III - JPC / BSD
15:45 - 15:55 : Task Descriptions and Results
Chenchen Ding and Toshiaki Nakazawa
15:55 - 16:07 : Korean to Japanese Neural Machine Translation System using Hanja Information
Hwichan Kim, Tosho Hirasawa and Mamoru Komachi
16:07 - 16:19 : Goku's Participation in WAT 2020
Dongzhe Wang and Ohnmar Htun
16:19 - 16:31 : The ADAPT Centre's Neural MT Systems for the WAT 2020 Document-Level Translation Task
Wandri Jooste, Rejwanul Haque and Andy Way
16:31 - 16:43 : The University of Tokyo's Submissions to the WAT 2020 Shared Task
Matīss Rikters, Toshiaki Nakazawa and Ryokan Ri
16:43 - 16:55 : Improving NMT via Filtered Back Translation
Nikhil Jaiswal, Mayur Patidar, Surabhi Kumari, Manasi Patwardhan, Shirish Karande, Puneet Agarwal and Lovekesh Vig
16:55 - 17:00Short Break
17:00 - 18:00Research Paper II
17:00 - 17:20 : A parallel evaluation data set of software documentation with document structure annotation
Bianka Buschbeck and Miriam Exel
17:20 - 17:40 : Inference-only sub-character decomposition improves translation of unseen logographic characters
Danielle Saunders, Weston Feely and Bill Byrne
17:40 - 18:00 : An Error-based Investigation of Statistical and Neural Machine Translation Performance on Hindi-to-Tamil and English-to-Tamil
Akshai Ramesh, Venkatesh Balavadhani Parthasa, Rejwanul Haque and Andy Way
18:00Closing
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POLICY

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RESEARCH PAPER

WAT 2020 invites researchers to submit their original work on machine translation for Asian languages. The scope covers studies and reports on theories, techniques, and resources to improve the machines translation of Asian languages. All submitted research papers will be examined under a double-blind peer-reviewing to decide if they will appear at the workshop. Topics of interest include, but are not limited to:

The format of research paper is identital to the format of system description, please refer to the section of PAPER SUBMISSION INFORMATION.

TRANSLATION TASK

Tasks: