Sahar Garoucy

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Emotion recognition from speech has noticeable applications in the speech-processing systems. In this paper, the effect of using a rich set of features including formant frequency related, pitch frequency related, energy, and the two first mel-frequency cepstral coefficients (MFCCs) on improving the performance of speech emotion recognition systems is(More)
The main contribution of this paper is to propose a nonlinear robust controller to synchronize general chaotic systems, such that the controller does not need the information of the chaotic system’s model. Following this purpose, in this paper, two methods are proposed to synchronize general forms of chaotic systems with application in secure communication.(More)
This paper studies the Lorenz hyperchaos synchronization and its application to improve the security of communication systems. Two methods are proposed to synchronize the general forms of hyperchaotic systems, and their performance in secure communication application is verified. These methods use the radial basis function (RBF)-based neural controllers for(More)
Reducing the computational complexity is desired in speech coding algorithms. In this paper, three neural gain predictors are proposed which can function as backward gain adaptation module of low delay-code excited linear prediction (LD-CELP) G.728 encoder, recommended by International Telecommunication Union-Telecom sector (ITU-T, formerly CCITT). Elman,(More)
Codebook search has high computational load in code excited linear prediction (CELP) speech coders. In this paper, a fuzzy ARTMAP neural network (FAMNN) is used to determine the best index of shape codebook in ITU-T G.728 speech coding algorithm. In this way, the gain value is calculated according to this index and the best index of gain codebook is(More)
Low delay-code excited linear prediction (LD-CELP) is an attractive algorithm in implementing vocoders in voice over Internet protocol networks. This algorithm has been proposed for the coding of speech at 16 kbps with toll quality. However, operation at transmission rates lower than 16 kbps is desirable, so that traffic can be accommodated during system(More)
In the family of CELP coders, codebook search has high computational complexity. In this paper, the codebook search in low delay-code excited linear prediction (LD-CELP) G.728 coder is performed by a multi-self organizing map (SOM) neural model. A modified-supervised SOM training algorithm is also used in this work. In this algorithm, the codebook vectors(More)
In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in(More)
– The computational complexity in many signal processing systems is due to codebook search that is a time-consuming process. Finding efficient codebook search methods has attracted many research efforts in the recent years. In this paper, we suggest a search codebook method based on the magnitude behavior of inverse filtered target signal (MBIFTS) and(More)
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