The paper reports on the existence of McKean's nonlinear processes and the related
propagation of chaos results for a class of one-dimensional (1-D) generalized Burgers-type …

In this paper, features extracted from modulation spectrogram are used to classify the
phonemes in Gujarati language. Modulation spectrogram which is a 2-dimensional (ie, 2-D) …

We explore the possibility of recognizing speech signals using a large collection of coarse
acoustic events, which describe temporal relations between a small number of local features …

In the research field of pattern recognition, especially in the signal classification, the process
of determining the suitable and the relevant feature is important to obtain the better …

This paper addresses the problem of classification of speech transition sounds. A number of
non parametric classifiers are compared, and it is shown that some non-parametric …

In this paper, we propose use of modulation spectrogram-based features for stop
consonants classification based on their place of articulation. Stop sounds are classified as …

The perfect learning exists. We mean a learning model that can be generalized, and
moreover, that can always fit perfectly the test data, as well as the training data. We have …

This paper proposes a hybrid wavelet–neural network approach to classify speech for
multifunctional control applications. The classification of the consonants (b, d, g) is the focus …

This paper compares wavelet and STFT analysis for a speakerindependent stop
classification task using the TIMIT database. In the designed experiment the HMM classifier …

Abstract In the classical Wiener-Kolmogorov prediction problem, one fixes a functional of the
“future” and seeks its best predictor (in the L 2-sense). In this paper we treat a variant of this …