Developing a Computer-facilitated Tool for Acquiring Near-synonyms in Chinese and English
Shixiao Ouyang, Helena Hong Gao and Soo Ngee Koh
Eighth International Conference on Computational Semantics (IWCS-8 2009)
Tilburg University, Netherlands, January 7-9, 2009
When differentiating near-synonyms of a class of words, cognitive strategies besides grammatical knowledge are often applied by native speakers. However, second language learners are found facing difficulties in distinguishing words that have similar meanings. The near-synonyms of physical action verbs (PA Verbs) for instance can be distinctive from each other in the way in which their actions are depicted, but in terms of semantic analysis and language acquisition, it is not an easy task to identify the nuances among near-synonyms. Dictionaries and language databases, such as WordNet or synonym dictionaries, can show a list of words that are semantically related, but they do not contain the differentiae that are crucial for the choice among near-synonyms. There have been studies focusing on the semantic analysis of word classes in both English and Chinese, but taking a language learner’s perspective to tackle the subtle differences among the near-synonyms of PA Verbs have hardly been done. With a cross referential application of both Chinese and English languages, we aim to develop a computer-facilitated language-learning tool for L2 learners to master different sub-classes of PA Verbs in Chinese and English.
Gao’s work on semantic decomposition of near-synonyms of PA Verbs provides a theoretical guideline and solid ground for designing an e-learning tool for L2 learners. To make the semantic representations abstract enough for the purpose of computing, a rule based model will be applied to quantify the semantic properties of each word and to build up a near-synonym database. By tracing through the decomposed semantic components of near-synonyms, the learners are able to appreciate the nuances among near-synonyms with more intuitional and cognitive understanding. The computational system serves as a good starting point for exploring e-learning tools in teaching and learning of near-synonyms.
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