Progress in Nonlinear Speech Processing by Jacqueline Walker, Peter Murphy (auth.), Yannis Stylianou,

By Jacqueline Walker, Peter Murphy (auth.), Yannis Stylianou, Marcos Faundez-Zanuy, Anna Esposito (eds.)

This publication constitutes of the foremost result of the ecu expense (European Cooperation within the box of clinical and Technical examine) motion 277: NSP, Nonlinear Speech Processing, operating from April 2001 to June 2005. those effects have been offered on the final assembly of the administration committee of price motion 277, held in Heraklion, Crete, Greece 1n September 2005 throughout the Workshop on Nonlinear Speech Processing, WNSP 2005.

The thirteen revised complete papers during this state of the art survey have been conscientiously reviewed and chosen for inclusion within the ebook and are preceded with an advent by way of the editors. The articles current overviews of the 4 years study combining linear and non linear ways for processing the speech sign. insurance comprises such components as speech research for speech synthesis, speech acceptance, speech-non speech discrimination and voice caliber overview, speaker recognition/verification from a average or changed speech sign, speech enhancement, and emotional nation detection.

The booklet presents an extra and/or another option to the conventional process of linear speech processing.

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Taking the Fourier transform of the logarithmic power spectrum yields a prominent peak corresponding to the high frequency source component and a broader peak corresponding to the low frequency formant structure. 1(b)). In present day processing the inverse Fourier transform of the log magnitude spectrum is generally taken to represent the cepstrum of voiced speech. The real cepstrum is defined as the inverse Fourier transform of the log of the magnitude spectrum: Cˆ ( t ) = ∞ j 2 π ft df . ∫ log | S ( f ) | e −∞ (6) Fig.

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The final harmonics-tonoise ratio is expressed in dBs. A further advantage of HNR estimation in the frequency domain is the ability to estimate HNR over a desired frequency band. The HNR is computed as ⎧ N/ 2 2 ⎫ ⎪ Si ⎪ ⎪⎪ ⎪⎪ i HNR = 10 log 10 ⎨ N/ 2 ⎬ ⎪ 2⎪ i N ⎪ ⎪ ⎩⎪ i =1 ⎭⎪ ∑ ∑ (2) where |Si| represents harmonic amplitudes, and |Ni| is the noise estimate. 3 Cepstrum-Based Methods Before examining the cepstral-based voice irregularity indices a brief introduction to the cepstrum of voiced speech is provided.

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