Features derived from Multi-Layer Perceptrons (MLPs) are becoming increasingly popular for speech recognition. This paper describes various schemes for applying these features to ...
J. Park, Frank Diehl, M. J. F. Gales, Marcus Tomal...
The autoregressive HMM has been shown to provide efficient parameter estimation and high-quality synthesis, but in previous experiments decision trees derived from a non-autoregre...
In this paper we evaluate a method for generating synthetic speech at high speaking rates based on the interpolation of hidden semi-Markov models (HSMMs) trained on speech data re...
Michael Pucher, Dietmar Schabus, Junichi Yamagishi
Many real-world sequence learning tasks require the prediction of sequences of labels from noisy, unsegmented input data. In speech recognition, for example, an acoustic signal is...
This paper is dedicated to the description and the study of a new feature extraction approach for emotion recognition. Our contribution is based on the extraction and the character...