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This book precipitated from my ``spectral modeling'' course which has been offered at the Center for Computer Research in Music and Acoustics (CCRMA) since 1984. The course originally evolved as a dissemination vehicle for spectral-oriented signal-processing research in computer music, aimed at beginning graduate students in computer music and engineering programs et al. Over the years it has become more of a tour of fundamentals in spectral audio signal processing, with occasional mention and citation of prior and ongoing related research. In principle, the only prerequisites are the first two books in the music signal processing series [264,263].

The focus of this book is on spectral modeling applied to audio signals. More completely, the principal tasks are spectral analysis, modeling, and resynthesis (and/or effects). We analyze sound in terms of spectral models primarily because this is what the human brain does. We may synthesize/modify sound in terms of spectral models for the same reason.

The primary tool for audio spectral modeling is the short-time Fourier transform (STFT). The applications we will consider lie in the fields of audio signal processing and musical sound synthesis and effects.

The reader should already be familiar with the Fourier transform and elementary digital signal processing. One source of this background material is [264]. Some familiarity with digital filtering and associated linear systems theory, e.g., on the level of [263], is also assumed.

There is a notable absence in this book of emphasis on audio coding of spectral representations. While audio coding is closely related, there are other books which cover this topic in detail (e.g., [273,16,159]). On the other hand, comparatively few works address applications of spectral modeling in areas other than audio compression. This book attempts to help fill that gap.

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``Spectral Audio Signal Processing'', by Julius O. Smith III, W3K Publishing, 2011, ISBN 978-0-9745607-3-1.
Copyright © 2020-07-26 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA),   Stanford University