alexa Comparison of parametric and non-parametric representations of speech for recognition
Engineering

Engineering

Journal of Telecommunications System & Management

Author(s): OB Tuzun, M Demirekler, KB Nakiboglu

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In this paper, we compare several feature sets based on the parametric and non-parametric representations of speech. Parametric representations are reflection coefficients, LPC derived cepstral coefficients (CCs) and line spectral frequencies (LSFs). Non-parametric representations are based on mel-frequency cepstral coefficients (MFCCs). These different representations are evaluated by their scores of recognition, for a speaker independent, isolated word recognizer based on hidden Markov models (HMMs).

This article was published in IEEE and referenced in Journal of Telecommunications System & Management

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