Abstract
In this chapter we will discuss feature extraction methods for speaker classification. We introduce linear predictive coding, mel frequency cepstral coefficients and wavelets and perform experimental studies on AURORA and TIMIT data. For the speaker identification task, we can show that wavelets are beneficial.
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Schacht, S., Koreman, J., Lauer, C., Morris, A., Wu, D., Klakow, D. (2007). Frame Based Features. In: Müller, C. (eds) Speaker Classification I. Lecture Notes in Computer Science(), vol 4343. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74200-5_13
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DOI: https://doi.org/10.1007/978-3-540-74200-5_13
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