半自動擷取中文動補式複合動詞及其英文翻譯

李小慧

doi:10.6342/NTU202000527

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半自動擷取中文動補式複合動詞及其英文翻譯

Semi-Automatic Identification of Chinese Resultative Verb Compounds and Their English Translation Equivalents

李小慧 , Masters　　Advisor：高照明　　

英文 DOI： 10.6342/NTU202000527

動補式複合動詞；語料庫翻譯研究；半監督機器學習；條件隨機域；機器翻譯； RVC ； resultative verb compound ； corpus-based translation studies ； semi-supervised machine learning ； conditional random fields ； machine translation

Abstract │ Reference (40) │ Altmetrics

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Drastic differences in sentence structure and grammar complicate Chinese to English translation, with one particularly inconspicuous grammatical feature of Mandarin Chinese significantly hindering an accurate English translation: The Resultative Verb Compound or RVC. An RVC is a combination of characters (often in pairs, but not always) in which the first character constitutes some action or manner verb, and the second some result, direction, or extent (e.g., 打斷, 坐下, 讀熟, etc.). Vast amount of research on RVCs with respect to the history of its formation or its function in modern Chinese grammar has been conducted, but little to no serious research has been carried out on RVCs in the field of corpus linguistics or translation studies.

This study is thus focused on the identification and subsequent translation of RVCs based on the Chinese novel《狼圖騰》by Jiang Rong and its English translation Wolf Totem by Howard Goldblatt, which was manually aligned by us at the paragraph level to form a parallel corpus. To identify RVCs within the first 18 chapters of a novel, we adopted a method of semi-supervised machine learning with the use of the CRF++ toolkit. By first manually tagging RVCs in the first chapter of the text to act as seeds and then affixing certain key features – NLPIR and NAER part-of-speech tags, the corresponding B, I, and E tags for character positioning in the beginning, middle, and endings of a word, and the RVC seeds – to each character in the first 18 chapters to create a training file, we were able to generate thousands of predicted RVCs in two separate experiments (Experiment 1 used NLPIR “parent” tags, and Experiment 2 used NLPIR “child” tags). We discovered the NLPIR “child” tags produced more accurate results when compared to the NLPIR “parent” tags.

Upon identifying the RVCs, we created an interface to find the English translations of the RVCs using the program Anymalign, which is a multilingual word aligner. Though the program was unable to find many of the RVCs due to their low frequency and the literary nature of the text provided, the interface program allows translation researchers and working translators to manually identify translation equivalents of Mandarin Chinese RVCs and study the different translations based on the previously-aligned parallel corpus.

Reference ( 40 ) 〈TOP〉

Anthony, L. (2017). AntPConc (Version 1.2.1) [Computer Software]. Tokyo, Japan: Waseda University. Available from https://www.laurenceanthony.net/software
Baker, M. (1993). Corpus Linguistics and Translation Studies: Implications and Applications. In Mona Baker, Gill Francis & Elena Tognini-Bonelli (Eds.) Text and Technology: In Honour of John Sinclair (pp. 233–50). Amsterdam: John Benjamins B.V.
Bishop, C. (2006). Pattern Recognition and Machine Learning. New York: Springer Publishing.
Chao, Y.R. (1968). A Grammar of Spoken Chinese. Berkeley: University of California Press.
Cook, A. (2014). A Linguistic Analysis of Selected Morpho-syntactic Features of Spoken Mandarin (Doctoral dissertation). Griffith University.

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