Fundamentals of speech recognition
Fundamentals of speech recognition
Pulsed neural networks
Collective excitation phenomena and their applications
Pulsed neural networks
Hebbian learning of pulse timing in the Barn Owl auditory system
Pulsed neural networks
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04
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Human social communication depends largely on exchanges of non-verbal signals, including non-lexical expression of emotions in speech. In this work, we propose a biologically plausible methodology for the problem of emotion recognition, based on the extraction of vowel information from an input speech signal and on the classification of extracted information by a spiking neural network. Initially, a speech signal is segmented into vowel parts which are represented with a set of salient features, related to the Mel-frequency cesptrum. Different emotion classes are then recognized by a spiking neural network and classified into five different emotion classes.