Crosslingual comparison of linguistic phenomenon in English, Japanese and Chinese

Recent trend in computational linguistics tend to focus on how to represent meaning. The availability of parallel corpus has allowed researchers to study how languages convey the same information in different ways. This study adopts a quantitative and qualitative method to study translation shifts i...

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Bibliographic Details
Main Author: Gao, Eshley Huini
Other Authors: Francis Bond
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/95736
http://hdl.handle.net/10220/9431
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Institution: Nanyang Technological University
Language: English
Description
Summary:Recent trend in computational linguistics tend to focus on how to represent meaning. The availability of parallel corpus has allowed researchers to study how languages convey the same information in different ways. This study adopts a quantitative and qualitative method to study translation shifts in the short novel – The Adventure of the Dancing Men. The parallel tri-text corpus in English-Japanese-Chinese is a sub-corpus of the NTU Multilingual Corpus. We tagged the concepts according to the senses in the WordNets, and annotated relationships between translation correspondents. The results show that 49.60% and 50.87% of distinct synsets in the English source text were linked in the English-Japanese and English-Chinese corpus respectively. Of the total linked concepts, 51.58% and 60.07% of them are exact correspondents of the source language in the English- Japanese and English-Chinese corpus correspondingly. The remaining contribute to evidence for translation shifts, which includes direct differentiation like hyponymy relationship to less straightforward variation like translation equivalents. The study also attempts to describe some of the translation shifts observed in the corpus. We estimate that more than half of the translation shifts were due to language differences, although translating style also played a part in the shifts. Data from this study can be used to train machine translation systems to produce more human-like translations. Second language learners of Japanese and Chinese can also take advantage of the data to learn how the same idea can be transmitted in different ways.