Mohamed Debyeche

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This paper investigate the influence of GSMEFR speech Data on the performance of a text independent Speaker Identification System (SIS) based on Gaussian Mixture Models (GMM) classifiers. The performance evaluation due to the use of the GSMEFR speech Data, obtained by passing the local ARADIGIT database through the GSM coder/decoder. The recognition(More)
This paper investigates the use of a Time Delay Neural Network (TDNN) as fuzzy vector quantizer to improve the Distributed scheme of HMM speech recognition. We investigate how to optimize the use of the Vector Quantization (VQ) by combining complementary preprocessing techniques based on multi-streams acoustic analysis. Then, in order to eliminate the(More)
(CHMM). The performance of the proposed speech recognition technique was assessed using the ARADIGT transcoding with its 8 kHz downsampledversion.The ARADIGIT database consists of 60 speakers (31 male speakers and 29 female speakers) pronouncing the ten Arabic digits, was built in order to conduct the necessary experiments. The obtained results show that(More)
This paper presents a framework for VOIP database generation and an investigation of the impact of VOIP characteristics on the accuracy of automatic speaker identification system. Exactly we study the impact of G711 and iLBC codec, and the influence of packet loss. A set of experiments are done on the generated databases to find the best feature extraction(More)