Acquiring Translational Equivalence from a Japanese-Chinese Parallel Corpus

摘要

This paper presents our work on acquiring translational equivalence from a Japanese-Chinese parallel corpus. We follow and extend existing word alignment techniques, including statistical model and heuristic model, in order to achieve a high performance. In addition to the statistics of the parallel corpus, the lexical knowledge of the language pair, such as orthographic cognates and bilingual dictionary are exploited. The implemented aligner is applied to the annotation of word alignment in the parallel corpus and the evaluation is conducted also. The experimental results prove the usability of the aligner in our task.