Word order correction for language transfer using relative position language modeling

Chao Hong Liu, Chung Hsien Wu, Matthew Harris

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Sentence correction has been an important and emerging issue in computer-assisted language learning. However, existing techniques based on grammar rules or statistical machine translation are still not robust enough to tackle the common incorrect word order errors in sentences produced by second language learners of Chinese. In this paper, a novel relative position language model is proposed to address this problem, for which a corpus of erroneous English-Chinese language transfer sentences along with their corrected counterparts is created and manually judged by human annotators. Experimental results show that compared to a scoring approach based on an n-gram language model and a phrase-based machine translation system, the performance in terms of BLEU scores of the proposed approach achieved improvements of 20.3% and 26.5% for the correction of word order errors resulting from language transfer, respectively.

Original languageEnglish
Title of host publicationProceedings - 2008 6th International Symposium on Chinese Spoken Language Processing, ISCSLP 2008
Pages33-36
Number of pages4
DOIs
Publication statusPublished - 2008
Event2008 6th International Symposium on Chinese Spoken Language Processing, ISCSLP 2008 - Kunming, China
Duration: 2008 Dec 162008 Dec 19

Publication series

NameProceedings - 2008 6th International Symposium on Chinese Spoken Language Processing, ISCSLP 2008

Other

Other2008 6th International Symposium on Chinese Spoken Language Processing, ISCSLP 2008
CountryChina
CityKunming
Period08-12-1608-12-19

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems
  • Software

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