Arabic digits speech recognition and speaker identification in noisy environment using a hybrid model of VQ and GMM

This paper presents an automatic speaker identification and speech recognition for Arabic digits in noisy environment. In this work, the proposed system is able to identify the speaker after saving his voice in the database and adding noise. The mel frequency cepstral coefficients (MFCC) is the best approach used in building a program in the Matlab platform; also, the quantization is used for generating the codebooks. The Gaussian mixture modelling (GMM) algorithms are used to generate template, feature-matching purpose. In this paper, we have proposed a system based on MFCC-GMM and MFCC-VQ Approaches on the one hand and by using the Hybrid Approach MFCC-VQ-GMM on the other hand for speaker modeling. The White Gaussian noise is added to the clean speech at several signal-to-noise ratio (SNR) levels to test the system in a noisy environment. The proposed system gives good results in recognition rate

Comparative Study between Several Direction of Arrival Estimation Methods , Journal of Telecommunications and Information Technology, 2014, nr 1

In this paper a comparative study, restricted to one-dimensional stationary case, between several Direction of Arrival (DOA) estimation algorithms of narrowband signals is presented. The informative signals are corrupted by an Additive White Gaussian Noise (AWGN), to show the performance of each method by applying directly the algorithms without pre-processing techniques such as forward-backward averaging or spatial smoothing

Focusing Operators and Tracking Moving Wideband Sources , Journal of Telecommunications and Information Technology, 2016, nr 4

In this paper, the localization of wideband source with an algorithm to track a moving source is investigated. To locate the wideband source, the estimation of two directions of arrival (DOA) of this source from two different arrays of sensors is used, and then, a recursive algorithm is applied to predict the moving source’s position. The DOA is estimated by coherent subspace methods, which use the focusing operators. Practical methods of the estimation of the coherent signal subspace are given and compared. Once the initial position is estimated, an algorithm of tracking the moving source is presented to predict its trajectory

Lorentzian Operator for Angular Source Localization with Large Array, Journal of Telecommunications and Information Technology, 2015, nr 4

Source localization problem consists of an ensemble of techniques that are used to obtain spatial information of present radiation in given medium of propagation, with a constraint of the antenna geometry and the characteristics of radiating sources. This condition gives multitude of cases to study, hence several methods were proposed in the literature. In this paper, a new algorithm for estimating the Direction of Arrival (DoA) of narrowband and far field punctual sources is introduced. By exploiting the spectrum of covariance matrix of received data, the Lorentzian function on spectral matrix to filter the eigenvalues is applied. This filtering process eliminates the eigenvalues belonging to signal subspace. Parameters of Lorentz function are adjusted using first and second statistics of eigenvalues. The algorithm requires the knowledge of minimum eigenvalue and is performing when the dimension of antenna is relatively large which is confirmed by several Monte Carlo simulations

Performance Comparison of Several Algorithms for Localization of Wideband Sources, Journal of Telecommunications and Information Technology, 2023, nr 3

In recent years, researchers have tried to estimate the direction-of-arrival (DOA) of wideband sources and several novel techniques have been proposed. In this paper, we compare six algorithms for calculating the DOA of broadband signals, namely coherent subspace signal method (CSSM), two-sided correlation transformation (TCT), incoherent multiple signal classification (IMUSIC), test of orthogonality of frequency subspaces (TOFS), test of orthogonality of projected subspaces (TOPS), and squared TOPS (S-TOPS). The comparison is made through computer simulations for different parameters, such as signal-to-noise ratio (SNR), in order to establish the efficiency and performance of the discussed methods in noisy environments. CSSM and TCT require initial values, but the remaining approaches do not need any preprocessing

Using Least Mean p-Power Algorithm to Correct Channel Distortion in MC-CDMA Systems, Journal of Telecommunications and Information Technology, 2018, nr 3

This work focuses on adaptive Broadband Radio Access Network (BRAN) channel identification and on downlink Multi-Carrier Code Division Multiple Access (MCCDMA) equalization. We use the normalized BRAN C channel model for 4G mobile communications, distinguishing between indoor and outdoor scenarios. On the one hand, BRAN C channel parameters are identified using the Least Mean p-Power (LMP) algorithm. On the other, we consider these coefficients in the context of adaptive equalization. We provide an overview and a mathematic formulation of MC-CDMA systems. According to these fundamental concepts, the equalizer technique is investigated analytically to compensate for channel distortion in terms of the bit error rate (BER). The numerical simulation results, for various signal-to-noise ratios and different p threshold, show that the presented algorithm is able to simulate the BRAN C channel measured with different accuracy levels. Furthermore, as far as the adaptive equalization problem is concerned, the results obtained using the zero-forcing equalizer demonstrate that the algorithm is adequate for some particular cases of threshold p

Channel Identification Using Chaos for an Uplink/Downlink Multicarrier Code Division Multiple Access System, Journal of Telecommunications and Information Technology, 2010, nr 1

A scheme of chaotic spreading sequence for multicarrier code division multiple access system (MC-CDMA) is proposed to estimate the transmission channel. This system spreads spectrum and identifies the channel, simultaneously. The proposed scheme uses a chaotic sequence generated by a logistic map as a training signal and estimate channel parameters according to dynamics of the chaotic sequence. Encoding data by chaotic sequences is first built and then the orthogonal codes are used to spread the encrypted data for multiusers scheme. At the reception, first the channel parameters are identified using a training chaotic sequence in order to equalize the received data, and then the encrypted information is decoded for the desired user. The studies reveal that the proposed system (chaos plus orthogonal codes) significantly outperforms the Walsh-Hadamard code spreading in MC-CDMA system. The performance of the system is considered in the multiuser case by means of simulation. The simulation result shows that the proposed chaotic code spreading approach for channel identification achieves significant improvement in the channel identification, comparing to using others training sequence or the least square method

Higher Order Cumulants for Identification and Equalization of Multicarrier Spreading Spectrum Systems, Journal of Telecommunications and Information Technology, 2011, nr 2

This paper describes two blind algorithms for multicarrier code division multiple access (MC-CDMA) system equalization. In order to identify, blindly, the impulse response of two practical selective frequency fading channels called broadband radio access network (BRAN A and BRAN E) normalized for MC-CDMA systems, we have used higher order cumulants (HOC) to build our algorithms. For that, we have focussed on the experimental channels to develop our blind algorithms able to simulate the measured data with high accuracy. The simulation results in noisy environment and for different signal to noise ratio (SNR) demonstrate that the proposed algorithms are able to estimate the impulse response of these channels blindly (i.e., without any information about the input), except that the input excitation is i.i.d. (identically and independent distributed) and non-Gaussian. In the part of MC-CDMA, we use the zero forcing and the minimum mean square error equalizers to perform our algorithms. The simulation results demonstrate the effectiveness of the proposed algorithms

A Novel Kernel Algorithm for Finite Impulse Response Channel Identification, Journal of Telecommunications and Information Technology, 2023, nr 2

Over the last few years, kernel adaptive filters have gained in importance as the kernel trick started to be used in classic linear adaptive filters in order to address various regression and time-series prediction issues in nonlinear environments.In this paper, we study a recursive method for identifying finite impulse response (FIR) nonlinear systems based on binary-value observation systems. We also apply the kernel trick to the recursive projection (RP) algorithm, yielding a novel recursive algorithm based on a positive definite kernel. For purposes, our approach is compared with the recursive projection (RP) algorithm in the process of identifying the parameters of two channels, with the first of them being a frequency-selective fading channel, called a broadband radio access network (BRAN B) channel, and the other being a a theoretical frequency-selective channel, known as the Macchi channel. Monte Carlo simulation results are presented to show the performance of the proposed algorith

Adaptive Algorithms Versus Higher Order Cumulants for Identification and Equalization of MC-CDMA, Journal of Telecommunications and Information Technology, 2014, nr 3

In this paper, a comparative study between a blind algorithm, based on higher order cumulants, and adaptive algorithms, i.e. Recursive Least Squares (RLS) and Least Mean Squares (LMS) for MultiCarrier Code Division Multiple Access (MC-CDMA) systems equalization is presented. Two practical frequency-selective fading channels, called Broadband Radio Access Network (BRAN A, BRAN B) normalized for MC-CDMA systems are considered. In the part of MC-CDMA equalization, the Zero Forcing (ZF) and the Minimum Mean Square Error (MMSE) equalizer techniques were used. The simulation results in noisy environment and for different signal to noise ratio (SNR) demonstrate that the blind algorithm gives approximately the same results obtained by adaptive algorithms. However, the proposed algorithm presents the advantage to estimate the impulse response of these channels blindly except that the input excitation is non-Gaussian, with the low calculation cost, compared with the adaptive algorithms exploiting the information of input and output for the impulse response channel estimation