Audio signal classification with temporal envelopes

The conventional approach to audio processing, based on the short-time power spectrum model, is not adequate when it comes to general audio signals. We propose an approach, justified by studies from psycho-acoustics and neuroimaging, which uses the magnitude and frequency envelope of the audio signal in the from of AM-FM modulations to build an ARMA model which is then fed to a GMM to classify into various audio classes. We show that it makes explicit certain aspects of the signal which are overlooked when processing is limited to the spectral domain.

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