Yi-Jyun Chen


2021

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Learning to Find Translation of Grammar Patterns in Parallel Corpus
Kai-Wen Tuan | Yi-Jyun Chen | Yi-Chien Lin | Chun-Ho Kwok | Hai-Lun Tu | Jason S. Chang
Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021)

We introduce a method for assisting English as Second Language (ESL) learners by providing translations of Collins COBUILD grammar patterns(GP) for a given word. In our approach, bilingual parallel corpus is transformed into bilingual GP pairs aimed at providing native language support for learning word usage through GPs. The method involves automatically parsing sentences to extract GPs, automatically generating translation GP pairs from bilingual sentences, and automatically extracting common bilingual GPs. At run-time, the target word is used for lookup GPs and translations, and the retrieved common GPs and their example sentences are shown to the user. We present a prototype phrase search engine, Linggle GPTrans, that implements the methods to assist ESL learners. Preliminary evaluation on a set of more than 300 GP-translation pairs shows that the methods achieve 91% accuracy.

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Identify Bilingual Patterns and Phrases from a Bilingual Sentence Pair
Yi-Jyun Chen | Hsin-Yun Chung | Jason S. Chang
Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021)

This paper presents a method for automatically identifying bilingual grammar patterns and extracting bilingual phrase instances from a given English-Chinese sentence pair. In our approach, the English-Chinese sentence pair is parsed to identify English grammar patterns and Chinese counterparts. The method involves generating translations of each English grammar pattern and calculating translation probability of words from a word-aligned parallel corpora. The results allow us to extract the most probable English-Chinese phrase pairs in the sentence pair. We present a prototype system that applies the method to extract grammar patterns and phrases in parallel sentences. An evaluation on randomly selected examples from a dictionary shows that our approach has reasonably good performance. We use human judge to assess the bilingual phrases generated by our approach. The results have potential to assist language learning and machine translation research.

2020

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改善詞彙對齊以擷取片語翻譯之方法 (Improving Word Alignment for Extraction Phrasal Translation)
Yi-Jyun Chen | Ching-Yu Helen Yang | Jason S. Chang
International Journal of Computational Linguistics & Chinese Language Processing, Volume 25, Number 2, December 2020

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Improving Phrase Translation Based on Sentence Alignment of Chinese-English Parallel Corpus
Yi-Jyun Chen | Ching-Yu Helen Yang | Jason S. Chang
Proceedings of the 32nd Conference on Computational Linguistics and Speech Processing (ROCLING 2020)