Abstract
This paper presents a parameterization technique of speech signal based on auditory filter modeling by the Gammachirp auditory filterbank (GcFB), which is designed to provide a spectrum reflecting the spectral properties of the cochlea filter, which is responsible of frequency analysis in the human auditory system. The center frequencies of the GcFB are based on the ERB-rate scale, with the bandwidth of the Gammachirp filter is measured in Equivalent Rectangular Bandwidth (ERB) of human auditory filters. Our parameterization approach gives interesting results vs. other standard techniques such as LPC (Linear Prediction Coefficients), PLP (Perceptual Linear Prediction), for recognition of isolated words of speech from the TIMIT database. The recognition system is implemented on HTK platform (Hidden Toolkit) based on the Hidden Markov Models with Gaussian Mixture observation continuous densities (HMM-GM).
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Zouhir, Y., Ouni, K. (2013). Speech Signals Parameterization Based on Auditory Filter Modeling. In: Drugman, T., Dutoit, T. (eds) Advances in Nonlinear Speech Processing. NOLISP 2013. Lecture Notes in Computer Science(), vol 7911. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38847-7_8
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DOI: https://doi.org/10.1007/978-3-642-38847-7_8
Publisher Name: Springer, Berlin, Heidelberg
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