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This paper introduces a fast learning method for a graphical probabilistic model for discrete speech recognition based on spoken Arabic digit recognition by means of a new proposed spanning tree structure that takes advantage of the temporal nature of speech signal. The experimental results obtained on a spoken Arabic digit dataset confirmed that for the… (More)
Mel Frequency Cepstral Coefficients (MFCCs) are the most popularly used speech features in many speech and speaker recognition applications. In this paper, we study the effect of the second-order derivatives of MFCC on the recognition of the Spoken Arabic digits. The system was developed using the Hidden Markov Models (HMMs) and Tree distribution… (More)
In this work we propose a novel method for automatic discrete speech recognition composed from two steps. In a first step, discrete speech features are extracted by means of Mel Frequency Cepstral Coefficients (MFCCs) followed by vector quantization (VQ). Then in a second step, the obtained features are fed to a Tree distribution classifier which provides… (More)
This paper presents automatic recognition of the Spoken Arabic Digits recognition by means of preselected parameters for the Hidden Markov Models using the cross validation method. The experimental results give the best result with the obtained parameters, achieve 94.09% correct digit recognition dataset and confirm the promising capabilities of the… (More)
Copula functions have been widely used in economics and finance and more recently it has been used in same field of pattern recognition. This paper presents an overview for introducing the use of Copulas function to supervised probabilistic classification applied to automatic speech recognition.
Arabic is a very widely spoken language but very few mining tools have been developed to exploit the data that lies within bodies of Arabic text. Thus, this paper presents a proposal of utilizing transitivity in the Arabic language to summarize texts written in Arabic.
In this paper, we investigate a new joint statistical model for text classification, which is copula functions, that is a way of formalizing dependence structures of random vectors. A copula is a distribution function with the implicit capacity to model nonlinear dependencies. Copula have been widely used in economics and finance and more recently it has… (More)
Language modeling for an inflected language such as Arabic poses new challenges for automatic speech recognition and related topic due to its rich morphology. A new technique for automatic speech recognition is presented in this paper. This technique employs a full measure of statistical dependence among random variables that is known as copulas. A novel… (More)
In this paper, we propose a new approach for the conception of a secure system of transmission synchronized by the chaos. Indeed, the message to be transmitted is inserted into the system of Chua while keeping its chaotic behavior. At the level of the receiver, and to estimate the message transmitted, we make appeal to a sliding mode observer who allows the… (More)