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A Sequence Alignment Model Based on the Averaged Perceptron

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Figure

Table 1: The training algorithm. Afunction under model parameterssequenceαis the affinity α , returning edit eand score v .
Table 2: Features with non-zero value for an exam-ple string pair and a model of order 2.
Table 3: Largest weights in a consonant-preservingedit affinity in which the first five consonants are
Table 5: Characteristics of the two transcription datasets, Arabic-English (A-E) and Mandarin-English
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