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Titlebook: Advances in Non-Linear Modeling for Speech Processing; Raghunath S. Holambe,Mangesh S. Deshpande Book 2012 The Author(s) 2012 AM-FM model.

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發(fā)表于 2025-3-21 18:26:18 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advances in Non-Linear Modeling for Speech Processing
影響因子2023Raghunath S. Holambe,Mangesh S. Deshpande
視頻videohttp://file.papertrans.cn/150/149204/149204.mp4
發(fā)行地址Nonlinear aspects of speech signals are covered in depth.Covers nonlinear modeling techniques from the context of speaker identification.New insight is explored to combine the speech production and sp
學(xué)科分類SpringerBriefs in Speech Technology
圖書封面Titlebook: Advances in Non-Linear Modeling for Speech Processing;  Raghunath S. Holambe,Mangesh S. Deshpande Book 2012 The Author(s) 2012 AM-FM model.
影響因子.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. .Differe
Pindex Book 2012
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https://doi.org/10.1057/9781403982391er Energy Operator is probably the field where most of the research regarding the operator has been done so far. Energy separation algorithm using TEO is then discussed and finally its noise suppression capability is presented.
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https://doi.org/10.1007/978-1-4899-7600-0l assumes that the sound source for the voiced speech is localized in the larynx and the vocal tract acts as a convolution filter for the emitted sound. Examples of phenomena not well-captured by the source-filter model include unstable airflow, turbulence and nonlinearities arising from oscillators with time-varying masses.
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Nonlinear Measurement and Modeling Using Teager Energy Operator,achtung gerade auf genaue Beibehaltung der Fragestellung und des Erhebungsobjektes geachtet werden mu?. Dies gilt selbst für die noch junge ?Panel?-Methode (s. u.), die ?u?erlich gesehen zwischen Marktuntersuchung und Marktbeobachtung zu stehen scheint.
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