Titlebook: Automatic Speech and Speaker Recognition; Advanced Topics Chin-Hui Lee,Frank K. Soong,Kuldip K. Paliwal Book 1996 Kluwer Academic Publisher

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https://doi.org/10.1007/978-3-319-72529-1erns or models for accurate pattern comparison. In this chapter, we discuss the issue of speech recognizer training from a broad perspective with root in the classical Bayes decision theory. We differentiate the method of classifier design by way of distribution estimation and the method of discrimi

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https://doi.org/10.1007/978-3-319-72529-1he relevant feature space(s). This is especially true in continuous speech and/or for speaker-independent tasks, where pronunciation variability is the greatest. In this chapter, we will discuss a number of clustering techniques which can be used to derive high quality acoustic prototypes.

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