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Paper Abstract and Keywords
Presentation 2018-12-11 14:15
Automatic Extraction of Bilingual Sentences by Similarity based on Earth Mover's Distance using Word Embeddings and Difference of Sentence Length
Ryo Tanoue, Hiroshi Echizen'ya (Hokkai-Gakuen Univ.), Kenji Araki (Hokkaido Univ.) NLC2018-30
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose new method to automatically extract bilingual sentences from comparable corpus without high quality bilingual knowledge such as bilingual dictionary. In our proposed method, the bilingual sentences are extracted using the translation matrix and the similarity between two language sentences based on the word embeddings. In that case, the Earth Mover's Distance is used to calculate the similarity. Moreover, the weight based on the difference of lengths between two language sentences is applied to the similarity in EMD. The evaluational experiments using the news article's comparable corpus indicate that the average of F-measure of our proposed method was 0.49, those of our proposed method without the weight based on the sentence length and the method based only on EMD were respectively 0.42, and that of the method using sentence length which is the baseline was 0.13. Therefore, we confirmed the effectiveness of our proposed method using the weight based sentence length.
Keyword (in Japanese) (See Japanese page) 
(in English) Bilingual Sentences / Automatic Extraction / word2vec / Earth Mover’s Distance / Sentence Length / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 355, NLC2018-30, pp. 3-8, Dec. 2018.
Paper # NLC2018-30 
Date of Issue 2018-12-04 (NLC) 
ISSN Online edition: ISSN 2432-6380
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Notes on Review This article is a technical report without peer review, and its polished version will be published elsewhere.
Download PDF NLC2018-30

Conference Information
Conference Date 2018-12-10 - 2018-12-12 
Place (in Japanese) (See Japanese page) 
Place (in English) Waseda Univ. Nishiwaseda Campus 
Topics (in Japanese) (See Japanese page) 
Topics (in English) The 5th Natural Language Processing Symposium & The 20th Spoken Language Symposium 
Paper Information
Registration To NLC 
Conference Code 2018-12-NLC-NL-SP-SLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic Extraction of Bilingual Sentences by Similarity based on Earth Mover's Distance using Word Embeddings and Difference of Sentence Length 
Sub Title (in English)  
Keyword(1) Bilingual Sentences  
Keyword(2) Automatic Extraction  
Keyword(3) word2vec  
Keyword(4) Earth Mover’s Distance  
Keyword(5) Sentence Length  
1st Author's Name Ryo Tanoue  
1st Author's Affiliation Hokkai-Gakuen University (Hokkai-Gakuen Univ.)
2nd Author's Name Hiroshi Echizen'ya  
2nd Author's Affiliation Hokkai-Gakuen University (Hokkai-Gakuen Univ.)
3rd Author's Name Kenji Araki  
3rd Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Speaker Author-1 
Date Time 2018-12-11 14:15:00 
Presentation Time 30 minutes 
Registration for NLC 
Paper # NLC2018-30 
Volume (vol) vol.118 
Number (no) no.355 
Page pp.3-8 
Date of Issue 2018-12-04 (NLC) 

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