Detecting Word Usage Errors in Chinese Sentences for Learning Chinese as a Foreign Language

Yow-Ting Shiue, Hsin-Hsi Chen


Abstract
Automated grammatical error detection, which helps users improve their writing, is an important application in NLP. Recently more and more people are learning Chinese, and an automated error detection system can be helpful for the learners. This paper proposes n-gram features, dependency count features, dependency bigram features, and single-character features to determine if a Chinese sentence contains word usage errors, in which a word is written as a wrong form or the word selection is inappropriate. With marking potential errors on the level of sentence segments, typically delimited by punctuation marks, the learner can try to correct the problems without the assistant of a language teacher. Experiments on the HSK corpus show that the classifier combining all sets of features achieves an accuracy of 0.8423. By utilizing certain combination of the sets of features, we can construct a system that favors precision or recall. The best precision we achieve is 0.9536, indicating that our system is reliable and seldom produces misleading results.
Anthology ID:
L16-1033
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
220–224
Language:
URL:
https://aclanthology.org/L16-1033
DOI:
Bibkey:
Cite (ACL):
Yow-Ting Shiue and Hsin-Hsi Chen. 2016. Detecting Word Usage Errors in Chinese Sentences for Learning Chinese as a Foreign Language. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 220–224, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Detecting Word Usage Errors in Chinese Sentences for Learning Chinese as a Foreign Language (Shiue & Chen, LREC 2016)
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PDF:
https://aclanthology.org/L16-1033.pdf