Spoken Language Processing: A Guide to Theory, Algorithm, and System Development
Spoken Language Processing: A Guide to Theory, Algorithm, and System Development
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In this article it is described the process to extract a set of cepstral coefficients from a warped frequency space (mel and bark) and analyze the perceived differences in the reconstructed signal. We will try to determine if there is any audible improvement between these two most used scales for the purpose of speech analysis by synthesis. We will use the same procedure for parameter extraction and signal reconstruction for both functions, replacing only the warping scale. The proposed system is based on a basic cepstral analysis synthesis model on the mel scale, whose excitation signal generation process has been changed. The inverse MLSA filter was obtained in order to generate the analysis signal, then this signal is fed into a wavelet decomposition block and the resultant coefficients are sent to the decoding system where the excitation signal is reconstructed. Furthermore the mel scale is replaced by bark scale.