The goal is to improve recognition rate by optimisation of Mel Frequency Cepstral Coe cients (MFCCs): modi cations concern the time-frequency representations used to estimate these coe cients. There are many ways to obtain a spectrum out of a signal which di er in the method itself (Fourier, Wavelets,...), and in the normalisation. We show here that we can obtain noise resistant cepstral coe ci...

in this paper, first, an initial feature vector for vocal fold pathology diagnosis is proposed. then, for optimizing the initial feature vector, a genetic algorithm is proposed. some experiments are carried out for evaluating and comparing the classification accuracies which are obtained by the use of the different classifiers (ensemble of decision tree, discriminant analysis and k-nearest neig...

Filter bank is the most common feature being employed in the research of the marginalisation approaches for robust speech recognition due to its simplicity in detecting the unreliable data in the frequency domain. In this paper, we propose a hybrid approach based on the marginalisation and the soft decision techniques that make use of the Mel-frequency cepstral coefficients (MFCCs) instead of f...

The automatic speaker verification spoofing and countermeasures challenge 2015 provides a common framework for the evaluation of spoofing countermeasures or anti-spoofing techniques in the presence of various seen and unseen spoofing attacks. This contribution proposes a system consisting of amplitude, phase, linear prediction residual, and combined amplitude phase-based countermeasures for the...

<span lang="EN-US">Speech recognition is one of the important applications artificial intelligence (AI). Speech aims to recognize spoken words regardless who speaking them. The process voice involves extracting meaningful features from and then classifying these into their classes. This paper presents a neural network classification system for Arabic letters. will study effect changing mu...

6 An analytical study of cepstral peak prominence (CPP) is presented, intended to provide an insight into its meaning and relation with voice perturbation parameters. To carry out this analysis, a parametric approach is adopted in which voice production is modelled using the traditional source-filter model and the first cepstral peak is assumed to have Gaussian shape. It is concluded that the m...

Ameliorating the performances of speech recognition system is a challenging problem interesting recent researchers. In this paper, we compare two extraction methods of Mel Frequency Cepstral Coefficients used to represent stressed speech utterances in order to obtain best performances. The first method known as traditional is based on single window (taper) generally the Hamming window and the s...