The goal of this work is to introduce an architecture to automatically detect the amount of stress in the speech signal close to real time. For this an experimental setup to recor...
This paper investigates the automatic recognition of emotion from spoken words by vector space modeling vs. string kernels which have not been investigated in this respect, yet. A...
We present a data-mining experiment on feature selection for automatic emotion recognition. Starting from more than 1000 features derived from pitch, energy and MFCC time series, ...
One of the biggest challenges in emotional speech resynthesis is the selection of modification parameters that will make humans perceive a targeted emotion. The best selection me...
Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...