Ahmed Ben Hamida

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This paper proposes two hybrid connectionist structural acoustical models for robust context independent phone like and word like units for speaker-independent recognition system. Such structure combines strength of Hidden Markov Models (HMM) in modeling stochastic sequences and the non-linear classification capability of Artificial Neural Networks (ANN).(More)
Current speech processing strategies for cochlear prosthesis system use filter bank structure in order to extract speech signal's energies relatively to the multiple frequency bands which are associated to the dedicated stimulation electrodes. This research concerned wavelet filtering module based on Mellin transform and dedicated to one cochlear speech(More)
  • Olfa Ben Sassi, Lamia Sellami, Mohamed Ben Slima, Khalil Chtourou, Ahmed Ben Hamida
  • 2013
In this paper, we will focus on the Spatial Gray Level Dependence Matrices SGLDM to extract the Haralick's texture features of the ultrasound breast lesions. This method relies on the manual selection of the region of interest, which results in the dependence of parameters values on the extracted region. For that reason, an improved Spatial Gray Level(More)
Bootstrap approach and Stochastic EM algorithm combination applied for the improvement of the multisource and multi-sensor image fusion process; was presented in this research. Improvement concerned not only image quality and reducing processing execution time as mentioned in our previous Bootstrap EM algorithm (BEM), but also regarding ini-tialization(More)
This paper presents two techniques of formants estimation based on LPC and cepstral analysis. These methods are implemented with Matlab and applied to the problem of accurate measurement of formant frequencies. The first algorithm estimate formant frequencies from the all pole model of the vocal tract transfer function. The approach relies on the source –(More)