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China Conference on Machine Translation (2020 :)

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Machine translation = 16th China Conference, CCMT 2020, Hohhot, China, October 10-12, 2020 : revised selected papers /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine translation/ edited by Junhui Li, Andy Way.
Reminder of title:	16th China Conference, CCMT 2020, Hohhot, China, October 10-12, 2020 : revised selected papers /
remainder title:	CCMT 2020
other author:	Li, Junhui.
corporate name:	China Conference on Machine Translation
Published:	Singapore :Springer Singapore : : 2020.,
Description:	xii, 143 p. :ill., digital ;24 cm.
[NT 15003449]:	Transfer Learning for Chinese-Lao Neural Machine Translation with Linguistic Similarity -- MTNER: A Corpus for Mongolian Tourism Named Entity Recognition -- Unsupervised Machine Translation Quality Estimation in Black-box Setting -- YuQ: A Chinese-Uyghur Medical-domain Neural Machine Translation Dataset Towards Knowledge-driven -- Quality Estimation for Machine Translation with Multi-granularity Interaction -- Transformer-based unified neural network for quality estimation and Transformer-based re-decoding model for machine translation -- NJUNLP's Machine Translation System for CCMT-2020 Uighur → Chinese Translation Task -- Description and Findings of OPPO's Machine Translation Systems for CCMT 2020 -- Tsinghua University Neural Machine Translation Systems for CCMT 2020 -- BJTU's Submission to CCMT 2020 Quality Estimation Task -- NJUNLP's Submission for CCMT20 Quality Estimation Task -- Tencent Submissions for the CCMT 2020 Quality Estimation Task -- Neural Machine Translation based on Back-Translation for Multilingual Translation Evaluation Task.
Contained By:	Springer Nature eBook
Subject:	Machine translating - Congresses. -
Online resource:	https://doi.org/10.1007/978-981-33-6162-1
ISBN:	9789813361621

Machine translation = 16th China Conference, CCMT 2020, Hohhot, China, October 10-12, 2020 : revised selected papers /
Machine translation16th China Conference, CCMT 2020, Hohhot, China, October 10-12, 2020 : revised selected papers /[electronic resource] :CCMT 2020edited by Junhui Li, Andy Way. - Singapore :Springer Singapore :2020. - xii, 143 p. :ill., digital ;24 cm. - Communications in computer and information science,13281865-0929 ;. - Communications in computer and information science ;1328..

Transfer Learning for Chinese-Lao Neural Machine Translation with Linguistic Similarity -- MTNER: A Corpus for Mongolian Tourism Named Entity Recognition -- Unsupervised Machine Translation Quality Estimation in Black-box Setting -- YuQ: A Chinese-Uyghur Medical-domain Neural Machine Translation Dataset Towards Knowledge-driven -- Quality Estimation for Machine Translation with Multi-granularity Interaction -- Transformer-based unified neural network for quality estimation and Transformer-based re-decoding model for machine translation -- NJUNLP's Machine Translation System for CCMT-2020 Uighur → Chinese Translation Task -- Description and Findings of OPPO's Machine Translation Systems for CCMT 2020 -- Tsinghua University Neural Machine Translation Systems for CCMT 2020 -- BJTU's Submission to CCMT 2020 Quality Estimation Task -- NJUNLP's Submission for CCMT20 Quality Estimation Task -- Tencent Submissions for the CCMT 2020 Quality Estimation Task -- Neural Machine Translation based on Back-Translation for Multilingual Translation Evaluation Task.

This book constitutes the refereed proceedings of the 16th China Conference on Machine Translation, CCMT 2020, held in Hohhot, China, in October 2020. The 13 papers presented in this volume were carefully reviewed and selected from 78 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.

ISBN: 9789813361621

Standard No.: 10.1007/978-981-33-6162-1doiSubjects--Topical Terms:

1004837
Machine translating
--Congresses.

LC Class. No.: P308 / .C45 2020

Dewey Class. No.: 418.020285

Machine translation = 16th China Conference, CCMT 2020, Hohhot, China, October 10-12, 2020 : revised selected papers /
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