By Jacqueline Walker, Peter Murphy (auth.), Yannis Stylianou, Marcos Faundez-Zanuy, Anna Esposito (eds.)
ISBN-10: 3540715037
ISBN-13: 9783540715030
ISBN-10: 3540715053
ISBN-13: 9783540715054
This ebook constitutes of the key result of the european price (European Cooperation within the box of medical and Technical learn) motion 277: NSP, Nonlinear Speech Processing, operating from April 2001 to June 2005. those effects have been provided on the final assembly of the administration committee of expense 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 cutting-edge survey have been conscientiously reviewed and chosen for inclusion within the booklet and are preceded with an creation by way of the editors. The articles current overviews of the 4 years examine combining linear and non linear methods for processing the speech sign. assurance contains such components as speech research for speech synthesis, speech attractiveness, speech-non speech discrimination and voice caliber evaluate, speaker recognition/verification from a usual or converted speech sign, speech enhancement, and emotional country detection.
The publication offers an extra and/or another option to the normal method of linear speech processing.
Read Online or Download Progress in Nonlinear Speech Processing PDF
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Extra resources for Progress in Nonlinear Speech Processing
Sample text
Given a shortterm discrete-time signal {x(n)}, n=0,1,…,N-1, the chirp Fourier transform X~ (ω ) is defined as: ( N −1 ~ X (ω ) = X ( z ) z = ρe jω = ∑ x(n) ρe jω n=0 ) −n ~ ~ = X (ω ) e jθ (ω ) (8) where ρ is the radius of the analysis circle. Similarly to Equation (1), the chirp group delay function CGD(ω) is defined as: ~ d (θ (ω )) (9) CGD(ω ) = − dω Interestingly enough, a fast Fourier transform (FFT) can be used to compute ~ X (ω ) by re-writing Equation (8) as: ( )( ) N −1 ~ X (ω ) = ∑ x(n) ρ − n e jω n =0 −n N −1 ( ) =∑~ x (n) e jω n=0 −n (10) Therefore, for the computation of the CGD(ω) of a given short-term signal, it is sufficient to term-wise multiply the signal samples with an exponential time-series and compute the group delay with direct formula in Equation (2).
The ZZT representation of the differential glottal flow signal (LF model [9]), which is shown in second column of Fig. 2, contains two groups of zeros: a group of zeros below R=1 (inside the unit circle) and a group of zeros above R=1 (outside the unit circle) in polar coordinates. The group of zeros inside the unit circle is due to the return phase of the glottal flow excitation waveform and the group outside the unit circle is due to the first phase of the LF signal. The zeros of the vocal tract filter response are mainly located inside the unit circle due to the decreasing exponential shape of this signal and there are gaps for the formant locations, which create formant spectral peaks.
6, for human speech peaks are sought at quefrency locations corresponding to the fundamental period and its multiples). 7. Sum each rahmonic in order to directly obtain the SRA index. Fig. 5. Estimation of cepstral peak prominence (CPP). Distance from regression line to prominent peak indicated CPP. 6 ampl. (arb. units) 4 2 0 -2 -4 -6 0 500 1000 1500 2000 -4 quefrency (s*10 ) Fig. 6. Estimation of sum of rahmonic amplitudes (SRA). Rahmonic peaks are located and summed (one sided cepstrum up to 1024 points) to produce SRA.
Progress in Nonlinear Speech Processing by Jacqueline Walker, Peter Murphy (auth.), Yannis Stylianou, Marcos Faundez-Zanuy, Anna Esposito (eds.)
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