Overview
- 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 speech perception systems
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Speech Technology (BRIEFSSPEECHTECH)
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Table of contents (6 chapters)
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Advances in Non-Linear Modeling for Speech Processing
Authors: Raghunath S. Holambe, Mangesh S. Deshpande
Series Title: SpringerBriefs in Speech Technology
DOI: https://doi.org/10.1007/978-1-4614-1505-3
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s) 2012
Softcover ISBN: 978-1-4614-1504-6Published: 21 February 2012
eBook ISBN: 978-1-4614-1505-3Published: 21 February 2012
Series ISSN: 2191-737X
Series E-ISSN: 2191-7388
Edition Number: 1
Number of Pages: XIII, 102
Number of Illustrations: 32 b/w illustrations
Topics: Signal, Image and Speech Processing, Natural Language Processing (NLP), Artificial Intelligence