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Evaluation of speaker identification system using GSMEFR speech data

Evaluation of speaker identification system using GSMEFR spe...

引用

5th Conference on Design and Technology of Integrated Systems in Nanoscale Era, DTIS 2010

作者： Krobba, Ahmed Debyeche, Mohamed Amrouche, Abederrahmane Speech Communication and Signal Processing Laboratory Faculty of Electronics and Computer Sciences USTHB P.O. Box 32 Bab Ezzouar Algiers Algeria

ISBN: (纸本)9781424463404

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 evaluation was also conducted using original ARADIGIT sampled at 16 KHz and its 8 KHz downsampled version. The ARADIGIT database consists of 60 speakers (31 men and 29 women) pronouncing the ten Arabic digits three times each. Different experiments were carried to measure the degradation introduced by different aspects of the simulated codec. © 2010 IEEE.

关键词： Loudspeakers

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ICA-based blind symbol detection for compound system MIMO-OFDM in CDMA context

ICA-based blind symbol detection for compound system MIMO-OF...

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2010 17th International Conference on Telecommunications, ICT 2010

作者： Hamza, A. Meftah, E.H. Chitroub, S. Touhami, R. Signal and Image Processing Laboratory Electronics and Computer Science Faculty USTHB Algiers Algeria Instrumentation Laboratory Electronics and Computer Science Faculty USTHB Algiers Algeria

ISBN: (纸本)9781424452477

Independent Component Analysis (ICA) based method for detection in the compound system MIMO-OFDM and in the context of CDMA is proposed. ICA algorithm is used as a post processor attached to a subspace based CDMA receiver. The proposed architecture of receiver reduces the bias caused by the channel noise and further decreases the noise by dimensionality reduction. A downlink CDMA based MIMO-OFDM channel is investigated given that only the code of the wanted mobile user is known. So, the blind symbol separation is then performed with the proposed receiver. We compare the proposed receiver and the ICA ability to the conventional matched filter, the wellknown linear MMSE receiver, the ZF detector. The obtained simulation results for the Additive White Gaussian Noise (AWGN) channel demonstrate that the proposed scheme achieves significant Bit Error Rate (BER) performance and is suitable for CDMA based MIMO-OFDM system. © 2009 IEEE.

关键词： Orthogonal frequency division multiplexing

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Evaluation of Speaker Identification System using GSMEFR speech Data

Evaluation of Speaker Identification System using GSMEFR spe...

引用

International Conference on Design and Technology of Integrated Systems in Nanoscale Era (DTIS)

作者： Ahmed Krobba Mohamed Debyeche Abederrahmane Amrouche Speech Communication and Signal Processing Laboratory Faculty of Electronics and Computer Sciences University of Sciences and Technology Houari Boumediene Algiers Algeria

ISBN: (纸本)9781424463381;9781424463404

关键词： speech analysis GSM Decoding Databases speech codecs signal design Mathematical model speech enhancement Wireless communication speech coding

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Performance evaluation of independent component analysis in an iris recognition system

Performance evaluation of independent component analysis in ...

引用

2010 ACS/IEEE International Conference on computer Systems and Applications, AICCSA 2010

作者： Bouraoui, Imen Chitroub, Salim Bouridane, Ahmed Signal and Image Processing Laboratory Electronics and Computer Science Faculty USTHB Algiers Algeria School of Computing Engineering and Information Sciences Northumbria University Pandon Building Newcastle Upon Tyne United Kingdom

ISBN: (纸本)9781424477159

The overall performance of any iris recognition system relies on the performance of its components, which are preprocessing, feature extraction and matching. Feature extraction is the important step of such recognition system, but it is strongly dependent on the pre-processing step that is consisting of localising and normalising the iris. In this paper, Independent Component Analysis (ICA), which is a recently developed statistical method for data analysis, is applied for extracting the features for iris region of interest that are statistically independent. Based on some mathematical criteria, the performance of ICA is evaluated by using two different subsets of CASIA-V3 iris image database. The obtained results are convincing and some future improved research works are subsequently envisaged.

关键词： Feature extraction

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Gaussian modeling and discrete cosine transform for efficient and automatic palmprint identification

Gaussian modeling and discrete cosine transform for efficien...

引用

1st International Conference on Machine and Web Intelligence, ICMWI 2010

作者： Meraoumia, Abdallah Chitroub, Salim Bouridane, Ahmed Signal and Image Processing Laboratory Electronics and Computer Science Faculty USTHB P.O. box 32 El Alia Bab Ezzouar 16111 Algeria School of Computing Engineering and Information Sciences Northumbria University Pandon Building Newcastle upon Tyne United Kingdom

ISBN: (纸本)9781424486113

Automatic personal identification using biometric information is playing a more and more important role in applications such as public security, access control, banking, etc. Palmprint identification is a subcategory of biometrics identification, which can efficiently used to identify the people. It is for this reason that palmprint-based identification is becoming increasingly popularity in recent years. In this paper, we present a novel scheme for palmprint identification using the multi-variate Gaussian Probability Density Function (GPDF) and two-dimensional Block based Discrete Cosine Transform (2D-BDCT). In this method, a palmprint is firstly divided into overlapping and equal-sized blocks, and then, applies the discrete cosine transform over each block. By using zigzag scan order (starting at the top-left) each transform block is reordered to produce the observation vector. Subsequently, we use the Gaussian probability density function for modeling the feature vector of each palmprint. Finally, Log-likelihood scores are used for palmprint matching. The proposed scheme is validated for their efficacy on PolyU palmprint database of 100 users. Our experimental results show the effectiveness and reliability of the proposed approach, which brings both high identification accuracy rate. © 2010 IEEE.

关键词： Biometrics

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Performance evaluation of Independent Component Analysis in an iris recognition system

Performance evaluation of Independent Component Analysis in ...

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ACS/IEEE International Conference on computer Systems and Applications

作者： Imen Bouraoui Salim Chitroub Ahmed Bouridane Signal and Image Processing Laboratory Electronics and Computer Science Faculty University of Sciences and Technology Houari Boumediene Algiers Algeria School of Computing Engineering and Information Sciences Northumbria University Newcastle-upon-Tyne UK

关键词： Iris recognition Feature extraction Entropy Iris Transforms Vectors Random variables

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Gaussian modeling and Discrete Cosine Transform for efficient and automatic palmprint identification

Gaussian modeling and Discrete Cosine Transform for efficien...

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International Conference on Machine and Web Intelligence (ICMWI)

作者： Abdallah Meraoumia Salim Chitroub Ahmed Bouridane Signal and Image Processing Laboratory Electronics and Computer Science Faculty University of Sciences and Technology Houari Boumediene Bab-Ezzouar Algeria School of Computing Engineering and Information Sciences Northumbria University Newcastle-upon-Tyne UK

关键词： Feature extraction Discrete cosine transforms Databases Accuracy Hidden Markov models Probability density function

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A two-mass model of the vocal cords: determination of control parameters

A two-mass model of the vocal cords: determination of contro...

引用

IEEE International Conference on Multimedia Computing and Systems (ICMCS)

作者： Hocine Teffahi Signal Processing and Speech communication laboratory Electronics and computer Sciences Faculty Houari Boumedienne University of Sciences and Technologies USTHB Algiers Algeria

We present numerical simulations performed with a two-mass model of the vocal folds. We use the model to compute the fundamental frequency as a function of two control parameters: subglottal pressure and vocal cords t... 详细信息

关键词： Frequency Pressure control Computational modeling computer simulation Larynx Springs communication system control signal processing Oral communication Laboratories

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Linear discriminant analysis for face recognition

Linear discriminant analysis for face recognition

引用

IEEE International Conference on Multimedia Computing and Systems (ICMCS)

作者： Fatma Zohra Chelali A. Djeradi R. Djeradi Speech Communication and Signal Processing Laboratory Electronics and Computer Sciences Faculty Houari Boumedienne University of Sciences and Technologies USTHB Algiers Algeria

Face is the most common biometric identifier used by humans. During the past thirty years, a number of face recognition techniques have been proposed, all of these methods focus on image-based face recognition that use a still image as input data. In this paper, Linear Discriminant Analysis (LDA) which is also called fisherface is an appearance-based technique used for the dimensionality reduction and recorded a great performance in face recognition. This method works on the same principle as the eigenface method (PCA).it performs dimensionality reduction while preserving as much of the class discriminatory information as possible. LDA makes use of projections of training images into a subspace defined by the fisher faces known as fiherspace. Recognition is performed by projecting a new face onto the fisher space, The KNN algorithm is then applied for identification.

关键词： Linear discriminant analysis Face recognition Independent component analysis Oral communication Biomedical signal processing Laboratories Humans Image recognition Principal component analysis Layout

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Integration of auxiliary features in Hidden Markov Models for Arabic speech recognition

Integration of auxiliary features in Hidden Markov Models fo...

引用

International Conference on signals, Circuits and Systems, SCS

作者： Anissa Imen Amrous Mohamed Debyeche A. Amrouche Speech Communication and Signal Processing laboratory (LPCTS) Faculty of Electronics and Computer Sciences University of Sciences and Technology Houari Boumediene Algiers Algeria

ISBN: (纸本)9781424443970;9781424443987

In this paper, the integration of auxiliary features in Hidden Markov Model (HMM) based Automatic speech Recognition (ASR) system is presented. In particular, we concentrate on the potential benefits of the combination of auxiliary features with standard acoustic parameters in adverse acoustic environments. The experiments were fulfilled using the HTK Toolkit and ARADIGIT corpus which is a data base of Arabic spoken words. The obtained results show that while the integration of the auxiliary features with the standard parameters by SI (Separate Integration) strategy leads to small improvements in the two test environments (clean and noisy), their integration by DI (Direct Integration) strategy leads to a significant improvement of the recognition system performance in noisy environment.

关键词： Hidden Markov models speech recognition Automatic speech recognition Mel frequency cepstral coefficient Acoustic noise Working environment noise Parameter extraction Cepstral analysis signal processing Filter bank

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