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Identifying Complex Sound Correspondences in Bilingual Wordlists

机译:识别双语单词表中的复杂声音对应

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The determination of recurrent sound correspondences between languages is crucial for the identification of cognates, which are often employed in statistical machine translation for sentence and word alignment. In this paper, an algorithm designed for extracting non-compositional compounds from bitexts is shown to be capable of determining complex sound correspondences in bilingual wordlists. In experimental evaluation, a C++ implementation of the algorithm achieves approximately 90% recall and precision on authentic language data.
机译:确定语言之间的重复声音对应关系对于识别同源词至关重要,而同源词通常在统计机器翻译中用于句子和单词对齐。在本文中,设计用于从bitexts中提取非成分化合物的算法被证明能够确定双语单词列表中的复杂声音对应关系。在实验评估中,该算法的C ++实现对真实语言数据实现了大约90%的查全率和精确度。

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