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Future Prospects

We have profitably used many of the known properties of the inner-ear in our spectral models. For example, the peak-dominance of audio perception matches well with the ``unreasonably effective'' sinusoidal model. Similarly, as MPEG audio and S+N+T models show, we can inaudibly eliminate over $ 90\%$ of the information in a typical sound, on average.

An interesting observation from the field of neuroscience is the following [82]:

``... most neurons in the primary auditory cortex A1 are silent most of the time ...''
This experimental fact indicates the existence of a much sparser high-level model for sound in the brain. We know that the cochlea of the inner ear is a kind of real-time spectrum analyzer. The question becomes how is the ``ear's spectrogram'' processed and represented at higher levels of audition, and how do we devise efficient algorithms for achieving comparable results?


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``Spectral Audio Signal Processing'', by Julius O. Smith III, W3K Publishing, 2011, ISBN 978-0-9745607-3-1.
Copyright © 2016-07-18 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA),   Stanford University
CCRMA