Data-driven lexical modeling of pronunciation variations for ASR
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چکیده
In this paper a method for the automatic construction of a lexicon with multiple entries per word is described. The basic idea is to transform a reference word transcription by means of stochastic pronunciation rules that can be learned automatically. This approach already proved its potential (Cremelie & Martens, 1999), and is now brought to a much higher level of performance. Relative reductions of the word error rate (WER) of 20 % (open vocabulary) to 45 % (closed vocabulary) are now within reach.
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تاریخ انتشار 2000