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Advances in Non-Linear Modeling for Speech Processing

Af: Raghunath S. Holambe, Mangesh S. Deshpande Engelsk Paperback

Advances in Non-Linear Modeling for Speech Processing

Af: Raghunath S. Holambe, Mangesh S. Deshpande Engelsk Paperback
Tjek vores konkurrenters priser

Advances in Non-Linear Modeling for Speech Processing includes advanced topics in non-linear estimation and modeling techniques along with their applications to speaker recognition.

Non-linear aeroacoustic modeling approach is used to estimate the important fine-structure speech events, which are not revealed by the short time Fourier transform (STFT). This aeroacostic modeling approach provides the impetus for the high resolution Teager energy operator (TEO). This operator is characterized by a time resolution that can track rapid signal energy changes within a glottal cycle.

The cepstral features like linear prediction cepstral coefficients (LPCC) and mel frequency cepstral coefficients (MFCC) are computed from the magnitude spectrum of the speech frame and the phase spectra is neglected. To overcome the problem of neglecting the phase spectra, the speech production system can be represented as an amplitude modulation-frequency modulation (AM-FM) model. To demodulate the speech signal, to estimation the amplitude envelope and instantaneous frequency components, the energy separation algorithm (ESA) and the Hilbert transform demodulation (HTD) algorithm are discussed.

Different features derived using above non-linear modeling techniques are used to develop a speaker identification system. Finally, it is shown that, the fusion of speech production and speech perception mechanisms can lead to a robust feature set.

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Advances in Non-Linear Modeling for Speech Processing includes advanced topics in non-linear estimation and modeling techniques along with their applications to speaker recognition.

Non-linear aeroacoustic modeling approach is used to estimate the important fine-structure speech events, which are not revealed by the short time Fourier transform (STFT). This aeroacostic modeling approach provides the impetus for the high resolution Teager energy operator (TEO). This operator is characterized by a time resolution that can track rapid signal energy changes within a glottal cycle.

The cepstral features like linear prediction cepstral coefficients (LPCC) and mel frequency cepstral coefficients (MFCC) are computed from the magnitude spectrum of the speech frame and the phase spectra is neglected. To overcome the problem of neglecting the phase spectra, the speech production system can be represented as an amplitude modulation-frequency modulation (AM-FM) model. To demodulate the speech signal, to estimation the amplitude envelope and instantaneous frequency components, the energy separation algorithm (ESA) and the Hilbert transform demodulation (HTD) algorithm are discussed.

Different features derived using above non-linear modeling techniques are used to develop a speaker identification system. Finally, it is shown that, the fusion of speech production and speech perception mechanisms can lead to a robust feature set.

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Produktdetaljer
Sprog: Engelsk
Sider: 102
ISBN-13: 9781461415046
Indbinding: Paperback
Udgave: 2012
ISBN-10: 1461415047
Kategori: Billedbehandling: systemer og teknologi
Udg. Dato: 21 feb 2012
Længde: 0mm
Bredde: 155mm
Højde: 235mm
Forlag: Springer-Verlag New York Inc.
Oplagsdato: 21 feb 2012
Forfatter(e): Raghunath S. Holambe, Mangesh S. Deshpande
Forfatter(e) Raghunath S. Holambe, Mangesh S. Deshpande

Kategori Billedbehandling: systemer og teknologi

ISBN-13 9781461415046

Sprog Engelsk

Indbinding Paperback

Sider 102

Udgave 2012

Længde 0mm

Bredde 155mm

Højde 235mm

Udg. Dato 21 feb 2012

Oplagsdato 21 feb 2012

Forlag Springer-Verlag New York Inc.

Kategori sammenhænge