Identifying Cognate Sets Across Dictionaries of Related Languages

机译：跨相关语言词典识别同源集

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We present a system for identifying cognate sets across dictionaries of related languages. The likelihood of a cognate relationship is calculated on the basis of a rich set of features that capture both phonetic and semantic similarity, as well as the presence of regular sound correspondences. The similarity scores are used to cluster words from different languages that may originate from a common proto-word. When tested on the Algonquian language family, our system detects 63% of cognate sets while maintaining cluster purity of 70%

机译：我们提出了一种用于跨相关语言词典识别同源集的系统。关联关系的可能性是根据捕获语音和语义相似性以及规则声音对应关系的丰富功能集计算得出的。相似度分数用于对可能来自共同原型词的不同语言的词进行聚类。在Algonquian语言家族中进行测试时，我们的系统检测到63％的同源集，同时保持70％的簇纯度

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《Conference on empirical methods in natural language processing》|2017年|2509-2518|共10页
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Adam St Arnaud; David Beck; Grzegorz Kondrak;
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Identifying Cognate Sets Across Dictionaries of Related Languages

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