Proceedings ArticleDOI
On a simple algorithm to calculate the 'energy' of a signal
J.F. Kaiser
- pp 381-384
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TLDR
The results of applying this algorithm to a number of well-known signals are shown and some of the invariance and noise properties of the algorithm are derived and verified by simulation.Abstract:
A simple algorithm is derived that permits on-the-fly calculation of the energy required to generate, in a certain sense, a signal. The results of applying this algorithm to a number of well-known signals are shown. Some of the invariance and noise properties of the algorithm are derived and verified by simulation. The implementation of the algorithm and its application to speech processing are briefly discussed. >read more
Citations
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Survey on speech emotion recognition: Features, classification schemes, and databases
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Energy separation in signal modulations with application to speech analysis
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Nonlinear feature based classification of speech under stress
TL;DR: Three new features derived from the nonlinear Teager (1980) energy operator (TEO) are investigated for stress classification and it is shown that the TEO-CB-Auto-Env feature outperforms traditional pitch and mel-frequency cepstrum coefficients (MFCC) substantially.