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Summary of LP Spectral Envelopes

In summary, the spectral envelope of the $ m$th spectral frame, computed by linear prediction, is given by

$\displaystyle {\hat Y}_m(\omega_k) \eqsp \frac{{\hat g}_m}{\left\vert{\hat A}_m\left(e^{j\omega_k }\right)\right\vert}
$

where $ {\hat A}_m$ is computed from the solution of the Toeplitz normal equations, and $ {\hat g}_m = \vert\vert\,{\hat E}_m\,\vert\vert _2$ is the estimated rms level of the prediction error in the $ m$th frame.

The stable, all-pole filter

$\displaystyle \frac{{\hat g}_m}{{\hat A}_m(z)}
$

can be driven by unit-variance white noise to produce a filtered-white-noise signal having spectral envelope $ {\hat g}_m/\vert{\hat A}_m(e^{j\omega_k })\vert$. We may regard $ {\hat g}_m/{\hat A}_m(e^{j\omega_k })$ (no absolute value) as the frequency response of the filter in a source-filter decomposition of the signal $ y_m(n)$.

It bears repeating that $ \log A(e^{j\omega_k })$ is zero mean when $ A(z)$ is monic and minimum phase (all zeros inside the unit circle). This means, for example, that $ \log {\hat g}_m$ can be simply estimated as the mean of the log spectral magnitude $ \log \vert Y_m(e^{j\omega_k })\vert$.

For best results, the frequency axis ``seen'' by linear prediction should be warped to an auditory frequency scale, as discussed in Appendix F. This has the effect of increasing the accuracy of low-frequency peaks in the extracted spectral envelope, in accordance with the nonuniform frequency resolution of the inner ear.


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Next: Spectral Envelope Examples

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About the Author: Julius Orion Smith III
Julius Smith's background is in electrical engineering (BS Rice 1975, PhD Stanford 1983). He is presently Professor of Music and Associate Professor (by courtesy) of Electrical Engineering at Stanford's Center for Computer Research in Music and Acoustics (CCRMA), teaching courses and pursuing research related to signal processing applied to music and audio systems. See http://ccrma.stanford.edu/~jos/ for details.


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