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Semantic Transliteration of Personal Names

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Table 2: Chinese character usage in 3 corpora. The numbers in brackets indicate the percentage of characters that are shared by at least 2 corpora
Table 3: Number of unique entries in training and test sets, categorized by semantic attributes
Table 5 summarizes the gender detection accura-cies using Eq. (11) assuming language of origin is known, Gs=arg max(|,)sGP S LL G∈=G
Table 8 compares the MRR performance of the semantic transliteration systems with different Soft decision refers to the incorporation of the lan-guage model scores into the transliteration process to improve the prior knowledge in Bayesian infer-ence

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