International Journal of Computational Linguistics & Chinese Language Processing, Volume 19, Number 1, March 2014
7492Authors
nan
Abstract
For languages where space cannot be a boundary of a word, such as Chinese and Vietnamese, word segmentation is always the task to be done first in a statistical machine translation system (SMT). The word segmentation increases the translation quality, but it causes many unknown words (UKW) in the target translation. In this paper, we will present a novel approach to translate UKW. Based on the meaning relationship between Chinese and Vietnamese, we built a model which based on the meaning of the characters forming the UKW before translating the UKW through the model. Experiments show that our method significantly improved the performance of SMT. Keywords: Chinese-Vietnamese SMT, Unknown Word, Sino-Vietnamese, Pure-Vietnamese, SVBUT Model, PVBUT Model. 1.
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International Journal of Computational Linguistics & Chinese Language Processing Aims and Scope International Journal of Computational Linguistics and Chinese Language Processing (IJCLCLP) is an international journal published by the Association for Computational Linguistics and Chinese Language Processing (ACLCLP). This journal was founded in August 1996 and is published four issues per year since 2005. This journal covers all aspects related to computational linguistics and speech/text processing of all natural languages. Possible topics for manuscript submitted to the journal include, but are not limited to: • Computational Linguistics • Natural Language Processing • Machine Translation • Language Generation • Language Learning • Speech Analysis/Synthesis • Speech Recognition/Understanding • Spoken Dialog Systems • Information Retrieval and Extraction • Web Information Extraction/Mining • Corpus Linguistics • Multilingual/Cross-lingual Language Processing Membership & Subscriptions If you are interested in joining ACLCLP, please see appendix for further information. Copyright © The Association for Computational Linguistics and Chinese Language Processing International Journal of Computational Linguistics and Chinese Language Processing is published four issues per volume by the Association for Computational Linguistics and Chinese Language Processing. Responsibility for the contents rests upon the authors and not upon ACLCLP, or its members. Copyright by the Association for Computational Linguistics and Chinese Language Processing. All rights reserved. No part of this journal may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical photocopying, recording or otherwise, without prior permission in writing form from the Editor-in Chief. Cover Calligraphy by Professor Ching-Chun Hsieh, founding president of ACLCLP Text excerpted and compiled from ancient Chinese classics, dating back to 700 B.C. This calligraphy honors the interaction and influence between text and language International Journal of Computational Linguistics and Chinese Language Processing vol. 19, no. 1, March 2014 Contents Papers A Novel Approach for Handling Unknown Word Problem in Chinese-Vietnamese Machine Translation...................................... Phuoc Tran, and DienDinh 1 Joint Learning of Entity Linking Constraints Using a Markov-Logic Network…………………....................................... Hong-Jie Dai, Richard Tzong-Han Tsai, and Wen-Lian Hsu 11 Linking Databases using Matched Arabic Names........................... Tarek El-Shishtawy 33 On the Use of Speech Recognition Techniques to Identify Bird Species…………………………………………………………….. Wei-Ho Tsai, and Yu-Zhi Xue 55 The Association for Computational Linguistics and Chinese Language Processing Computational Linguistics and Chinese Language Processing Vol. 19, No. 1, March 2014, pp. 1-10 1 The Association for Computational Linguistics and Chinese Language Processing A Novel Approach for Handling Unknown Word Problem in Chinese-Vietnamese Machine Translation Phuoc Tran, and Dien Dinh Abstract For languages where space cannot be a boundary of a word, such as Chinese and Vietnamese, word segmentation is always the task to be done first in a statistical machine translation system (SMT). The word segmentation increases the translation quality, but it causes many unknown words (UKW) in the target translation. In this paper, we will present a novel approach to translate UKW. Based on the meaning relationship between Chinese and Vietnamese, we built a model which based on the meaning of the characters forming the UKW before translating the …
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Labeled Text
For languages where space cannot be a boundary of a word, such as Chinese and Vietnamese, word segmentation is always the task to be done first in a statistical machine translation system (SMT). The word segmentation increases the translation quality, but it causes many unknown words (UKW) in the target translation. In this paper, we will present a novel approach to translate UKW. Based on the meaning relationship between Chinese and Vietnamese, we built a model which based on the meaning of the characters forming the UKW before translating the UKW through the model. Experiments show that our method significantly improved the performance of SMT. Keywords: Chinese-Vietnamese SMT, Unknown Word, Sino-Vietnamese, Pure-Vietnamese, SVBUT Model, PVBUT Model. 1.
Publication Details
- Paper ID:
- 7492
- Year:
- 2014
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan