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Erschienen in:
Introduction to Speech Processing Kapitel lesen Erstes Kapitel lesen

2008 | OriginalPaper | Buchkapitel

12. The STFT, Sinusoidal Models, and Speech Modification

verfasst von : Michael M. Goodwin, Ph.D

Erschienen in: Springer Handbook of Speech Processing

Verlag: Springer Berlin Heidelberg

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Abstract

Frequency-domain signal representations are used for a wide variety of applications in speech processing. In this Chapter, we first consider the short-time Fourier transform (STFT), presenting a number of interpretations of the analysis-synthesis process in a consistent mathematical framework. We then develop the sinusoidal model as a parametric extension of the STFT wherein the data in the STFT is compacted, sacrificing perfect reconstruction at the benefit of achieving a sparser and essentially more meaningful representation. We discuss several methods for sinusoidal parameter estimation and signal reconstruction, and present a detailed treatment of a matching pursuit algorithm for sinusoidal modeling. The final part of the Chapter addresses speech modifications such as filtering, enhancement, and time-scaling, for which both the STFT and the sinusoidal model are effective tools.

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Vorheriges Kapitel Formant Estimation and Tracking
Nächstes Kapitel Adaptive Blind Multichannel Identification
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Metadaten
Titel
The STFT, Sinusoidal Models, and Speech Modification
verfasst von
Michael M. Goodwin, Ph.D
Copyright-Jahr
2008
Verlag
Springer Berlin Heidelberg
Buch
Springer Handbook of Speech Processing

Print ISBN: 978-3-540-49125-5

Electronic ISBN: 978-3-540-49127-9

Copyright-Jahr: 2008

DOI
https://doi.org/10.1007/978-3-540-49127-9_12

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