Automatic Classification of the “De” Word Usage for Chinese as a Foreign Language

7484

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nan

Abstract

This paper proposed a word usage classification for “De” in Chinese as a secondary language by rule induction algorithm. Learning of Chinese characters and tone adaption are both essential and hard tasks for non-native speakers. The frequent terms, defined in morphosyntatic particle “De” with three characters {的, 得, 地}, is hard to learn for foreign learners due to the similar pronunciation and meaning. This investment illustrates a data-driven algorithm to classify the usages about the morphosyntatic particle “De” in Chinese learning. Rule induction is one of the most important techniques to learn the knowledge from data. Since regularities hidden in data are frequently expressed in terms of rules, rule induction is one of the fundamental tools for natural language processing and obtains a significant improvement in character selection. By the automatic rule induction process, 32 rules are adopted here to classify the character usage in morphosyntatic particle “De.” According to the experimental results, we find the proposed method can provide good enough performance to classify the character usages for morphosyntatic particle “De.” Keywords: Rule Induction, Natural Language Processing, Secondary Language Learning, Classifier, Word Usage. 1.

Keywords

nan

Full Content

Computational Linguistics and Chinese Language Processing Vol. 20, No. 1, June 2015, pp. 65-78 65  The Association for Computational Linguistics and Chinese Language Processing Automatic Classification of the “De” Word Usage for Chinese as a Foreign Language Jui-Feng Yeh and Chan-Kun Yeh ABSTRACT This paper proposed a word usage classification for “De” in Chinese as a secondary language by rule induction algorithm. Learning of Chinese characters and tone adaption are both essential and hard tasks for non-native speakers. The frequent terms, defined in morphosyntatic particle “De” with three characters {的, 得, 地}, is hard to learn for foreign learners due to the similar pronunciation and meaning. This investment illustrates a data-driven algorithm to classify the usages about the morphosyntatic particle “De” in Chinese learning. Rule induction is one of the most important techniques to learn the knowledge from data. Since regularities hidden in data are frequently expressed in terms of rules, rule induction is one of the fundamental tools for natural language processing and obtains a significant improvement in character selection. By the automatic rule induction process, 32 rules are adopted here to classify the character usage in morphosyntatic particle “De.” According to the experimental results, we find the proposed method can provide good enough performance to classify the character usages for morphosyntatic particle “De.” Keywords: Rule Induction, Natural Language Processing, Secondary Language Learning, Classifier, Word Usage. 1. Introduction To learn Chinese as a foreign or second language is to study of the Chinese languages by non-native speakers and new learners. Increasing interested peoples in China learning from those outside has led to a corresponding interest in the study of Chinese as their second language, the official languages of mainland China and Taiwan. However, the learning of Chinese both within and outside China is not a recent phenomenon. Westerners started learning different Chinese languages in the 16th century. Within China, Mandarin became the  Department of Computer Science and Information Engineering, National Chiayi University, Chiayi city, Taiwan, ROC E-mail: Ralph@mail.ncyu.edu.tw 66 Jui-Feng Yeh & Chan-Kun Yeh official language in early 20th century. According to the analysis of Summer Institute for Linguistics (SIL), there are near to seven thousands languages over the world nowadays. Among these languages, the top five languages are Chinese, English, Spanish, Bengali and Indian by their population sizes. As the first and second languages, Chinese occupies 14.8 percents populations to be the most used language. China’s growing global influence has prompted a surge of interest in learning Mandarin Chinese as a foreign language (CFL), and this trend is expected to continue. Therefore, the population to learn Chinese as the second language is increasing in the latest decades (Simpson, 2000). Compared to the alphabetic language, Chinese is more complex and hard to understand for non-native speakers due to its several thousand characters and complicated sentence structures. Due the historical evolution of Chinese is deep and far, there are some word usage is susceptible to the corresponding allusions. Therefore, it is hard for the second language learners without …

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Labeled Text

This paper proposed a word usage classification for “De” in Chinese as a secondary language by rule induction algorithm. Learning of Chinese characters and tone adaption are both essential and hard tasks for non-native speakers. The frequent terms, defined in morphosyntatic particle “De” with three characters {的, 得, 地}, is hard to learn for foreign learners due to the similar pronunciation and meaning. This investment illustrates a data-driven algorithm to classify the usages about the morphosyntatic particle “De” in Chinese learning. Rule induction is one of the most important techniques to learn the knowledge from data. Since regularities hidden in data are frequently expressed in terms of rules, rule induction is one of the fundamental tools for natural language processing and obtains a significant improvement in character selection. By the automatic rule induction process, 32 rules are adopted here to classify the character usage in morphosyntatic particle “De.” According to the experimental results, we find the proposed method can provide good enough performance to classify the character usages for morphosyntatic particle “De.” Keywords: Rule Induction, Natural Language Processing, Secondary Language Learning, Classifier, Word Usage. 1.

Publication Details

Paper ID:
7484
Year:
2015
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan