SALAH Khennouf

AZIZI Mohammed , LABZA Nasreddine, MESSAAD Salim

Early Enhancing Diabetes Diagnosis using Machine Learning, Deep Learning Models, and Clinical Data Analysis

HADJAB Safwan , BENSEDDIK Mohamed

Amélioration de l'efficacité des cellules solaires photovoltaïques à base de Pérovskites

BENAMOR Imad Eddine , BOUDJELLAL Fadi

Access Control Using Specific Code and Biometric Identification

Djaidja Asma , Hadjab Dounya Ishraq

Study and Simulation of Losses in an Optical Fiber Connection with Application

Aroussi Wiam , Bouafia Dhahbia

Fabrication de Bio-Antigel avec Système de Pulvérisation Automatique Amélioré

BELDJOUDI Bochra , GAHAM Sabrina

Authorship Attribution of Specific Arabic Texts using Character N-gram and Classification Techniques

BARKA Riyadh , FERHAT Zeyd

Automatic System for Lip Reading Transcription

AZAZ Ayat Errahmen , BENDJEDDOU Omayma

Détection et localisation des défauts non francs dans les réseaux à base de câbles coaxiaux par la réflectométrie et la corrélation soustractive

HERIZI Sohaib , MIMOUNE Soheyb

Acquisition des données textuelles à l’aide de transcripteurs automatiques en vue d’une identification d’auteurs basée sur la fréquence des mots et l’intelligence artificielle.

OUCHENE Marouane , ADJENEG Mustapha

Mise en œuvre d’un kit didactique d’un générateur éolien et conception d’une interface d’acquisition et de supervision.

CHABBI Imane , REBANI Samia

Système d’Authentification d’Auteurs des Textes Arabes basé sur la SMO-SVM et la distance de Manhattan

GASMI Sohaib

Détection et localisation des défauts dans les Réseaux électriques filaires par la réflectométrie et les réseaux de neurones

BADREDDINE Rihab , CHERIKI Dalila

Amélioration de la caractéristique optique et électrique d'une cellule photovoltaïque à base de pérovskite

BACHA Bochra , HADLI Imane

Attribution d’auteurs des textes arabes traduits en plusieurs langues en utilisant les traducteurs automatiques

BELHADJ Mohammed , BOUREZG Ala Eddine

Evaluation de la robustesse d’attribution en reconnaissance d’auteur

CHENNI Ahmed Badis , CHARIF Abderrazak

Analyse et synthèse d’un signal de parole par la Matrice de Pencil en vue d’une discrimination de locuteurs.

MENASRI Radja , YAKOUBI Mebarka

Etude et analyse des effets d'acquisition optique à l'aide d'un OCR des textes arabes sur l’attribution d’auteurs

Zohir BACHIR , Ahmed BEDDAR

Conception et réalisation d’une interface Homme-Machine pour l’observation du processus de refonte d’Aluminium à ALGAL-Plus à base de l'automate (ET200S) et du logiciel TIA portal.

MECHTA Douaa , GHERBI Radhwane

Automatisation des tâches domotiques d’une maison à l’aide d’une carte Arduino et LabView

BENYAHIA Abdelkader

Etude et analyse sur les performances des techniques d’identification d’auteurs à partir des documents écrits et des documents transcrits

Most conventional approaches to Authorship Attribution (AA) rely on statistical methods and classification algorithms that utilize stylistic features extracted from textual document. These features may include lexical, syntactic, structural, and content-based markers that reflect an author’s unique writing style. In recent years, Pre-trained Language Models (PLMs) have gained significant attention in the field of text classification. While they have demonstrated strong performance on large-scale datasets and short texts, their effectiveness in scenarios with limited data—particularly in the context of Arabic Authorship Attribution (AAA)—remains insufficiently explored. This study aims to evaluate the effectiveness of state-of-the-art Pre-trained Arabic Transformer-based Models in handling imbalanced textual datasets, with a particular focus on the underrepresented domain of theological law, which has witnessed limited contributions in the context of AA. The study addresses AAA using imbalanced corpora containing texts of varying lengths, extracted from several books written by Arab authors who lived during the same historical period. We conducted several experiments involving the fine-tuning of four Pre-trained Arabic Transformer-based Models: AraBERT, AraELECTRA, ARBERT, and MARBERT. The obtained experimental results have shown that AraBERT achieved the best performance in attributing texts to their respective authors.

Citation

Salah KHENNOUF , Mounir BOURAS , ABDELHAFID Benyounes , ,(2026-01-29), Towards Robust Arabic Authorship Attribution: A Transformer-Based Model for Multi-Author Imbalanced Corpora,9th International Conference of Mathematical Sciences (ICMS 2025),Turkey

abstract:Authorship Attribution (AA) seeks to identify the author of a text by analyzing distinctive linguistic and stylistic features. While several studies have focused on English and other Latin-based languages, Arabic AA -particularly with imbalanced datasets- remains comparatively underexplored. In order to close this gap, this work uses a newly created dataset entitled SAB-2, which consists of 7 Arabic books with varying segment lengths, to examine the effectiveness of Arabic pretrained transformer models for multi-class AA. Given the strong impact of data imbalance on classification performance, we apply the Synthetic Minority Oversampling Technique (SMOTE) to enhance minority-class representation and examine its influence on model accuracy. Our experiments evaluate several transformer-based models -AraBERT, AraELECTRA, ARBERT, and MARBERT- alongside deep learning architectures (LSTM, CNN, and a hybrid LSTM-CNN model). Results show that SMOTE substantially improves performance across all models, with the LSTMCNN architecture combined with AraBERT achieving the highest accuracy of 89%, outperforming baseline experiments without balancing. The obtained results show the robustness of Arabic pretrained transformers in capturing stylistic features from limited and imbalanced textual data, highlighting their potential for advancing Arabic AA in resource-constrained domains.

Citation

Salah KHENNOUF , Mounir BOURAS , ABDELHAFID Benyounes , , (2026-01-25), Towards Robust Arabic Authorship Attribution: A Transformer-Based Model for Multi-Author Imbalanced Corpora, Bol. Soc. Paran. Mat., Vol:43, Issue:7, pages:10, SPM:www.spm.uem.br/bspm

In recent years, significant advancements have been made in thin-film planar heterojunction solar cells, emerging as cost-effective photovoltaic devices with high power conversion efficiency. Among the materials utilized, organometal trihalide perovskite (CH3NH3PbI3) stands out as a promising absorber material. Its appeal lies in the affordability of organic-inorganic perovskite compounds, readily available in nature, ease of fabrication, and compatibility with large-scale processing at low temperatures. In addition to its effective absorption in the ultraviolet range, this material exhibits captivating optoelectronic properties, including high crystallinity, elevated carrier mobility, and extensive carrier diffusion lengths. Despite these advantages, the highest reported power conversion efficiency for perovskite solar cells is currently at 26.1/100 , as of 2022. This study introduces a thin-film organometal trihalide perovskite solar cell featuring hybrid interfaces between carefully chosen materials. These selections are the result of an in-depth study aimed at minimizing recombination and optimizing performance. Furthermore, we enhance the absorption of the incident solar spectrum by incorporating a 1D photonic crystal at the cell’s bottom, facilitating the photon recycling process. The proposed solar cell parameters are numerically computed using the rigorous coupled wave algorithm through the SYNOPSYS RSOFT CAD tool. The thickness of each layer in the structure is optimized using the MOST scanning and optimization module of the RSOFT CAD tool, achieving the highest power conversion efficiency at a minimal device thickness (approximately 2.5 m). Remarkably, the power conversion efficiency achieved is 27.5/100, with a fill factor of 87.4/100 at AM 1.5, showcasing great promise. This demonstrates the remarkable potential of the proposed design to achieve efficiencies exceeding 5/100, positioning it as a competitive contender in the existing crystalline silicon photovoltaic market.

Citation

Mounir BOURAS , Salah KHENNOUF , ABDELHAFID Benyounes , ,(2026-01-25), Improve efficiency of Perovskite-Based Solar Cell,9th International Conference of Mathematical Sciences (ICMS 2025),TURKEY

Enhanced light trapping in thin-films perovskite solar cells by photonic crystal structures

Citation

Salah KHENNOUF , , (2025-12-30), Enhanced light trapping in thin-films perovskite solar cells by photonic crystal structures, AIPAvances, Vol:16, Issue:1, pages:11, AIP

Thin-film planar heterojunction perovskite solar cells have emerged as promising candidates for next-generation photovoltaic technologies due to their low fabrication cost and high power conversion efficiency (PCE). Among the various materials explored, perovskite (CH3NH3PbI3) based solar cell considering n-i-p structure, stands out as a highly efficient absorber owing to their favorable optoelectronic properties, including high crystallinity, superior carrier mobility, and long diffusion lengths. Despite these advantages, the highest reported PCE for such cells remains at 24.3% (as of 2024). In this work, we present a novel thin-film perovskite solar cell design incorporating hybrid material interfaces and a one-dimensional photonic crystal at the device’s rear side to enhance photon recycling and reduce carrier recombination. Numerical simulations are performed using the Rigorous Coupled Wave Analysis (RCWA) method via the SYNOPSYS RSoft CAD tool, with layer thicknesses optimized using the MOST scanning and optimization module. The proposed architecture achieves a PCE of 22.5% with a fill factor of 89.3% under AM 1.5 solar conditions and a total device thickness of approximately 2.5 um. These results highlight the potential of the proposed design to surpass the 20% efficiency benchmark and offer a competitive alternative to conventional crystalline silicon photovoltaics.

Citation

Moufdi Hadjab , Mounir BOURAS , Salah KHENNOUF , ABDELHAFID Benyounes , , (2025-12-15), Improve Efficiency of Perovskite-Based Solar Cell by Photon Recycling, Boletim da Sociedade Paranaense de Matemática, Vol:43, Issue:7, pages:1-10, Sociedade Brasileira de Matematica

Speaker recognition has emerged as a promising biometric approach for secure and contactless access control. This paper presents a comparative analysis of two widely used acoustic feature extraction techniques Mel-Frequency Cepstral Coefficients (MFCC) and Perceptual Linear Predictive (PLP) coefficients for speaker recognition systems based on Convolutional Neural Networks (CNNs). The proposed system is designed to classify speaker identities by analyzing short voice samples in a controlled access scenario. Both MFCC and PLP features were extracted from a curated dataset and used to train identical CNN architectures to ensure fair performance evaluation. The models were assessed based on accuracy, precision, recall, and training convergence. Experimental results demonstrate that while both feature sets provide strong classification performance, MFCC features yielded slightly higher accuracy and faster training convergence in our tests. These findings highlight the effectiveness of CNNs in voice-based biometric systems and provide valuable insights into feature selection for real-time, secure access control applications.

Citation

Salah KHENNOUF , ,(2025-12-10), Speaker Recognition for Access Control: A Comparative Analysis of MFCC and PLP Features using CNN-Based Classification,The 2nd International Conference on Advanced Technology in Electronic and Electrical Engineering,جامعة محمد بوضياف-المسيلة

Rolling element bearings are essential components in heavy-duty machinery such as drilling rigs, mining equipment, wind turbine rotors, and helicopter swash plates. Their failure can cause costly downtime and major repairs, making early fault detection and continuous monitoring critical. Traditional vibration-based methods, although widely applied, often struggle to identify incipient faults under variable operating conditions. Acoustic Emission (AE) sensing has emerged as a promising alternative, offering high sensitivity to microscopic damage and transient events. However, many AE-based diagnostic approaches rely on characteristic fault frequency extraction, which requires precise information about rotational speed and bearing geometry, limiting their practicality. This study introduces an AE-based fault localization method that combines wavelet-derived features with a Random Forest classifier. Experiments on the UOREDAFCLS dataset show that energy-based features achieve nearperfect classification accuracy across different fault types. The results highlight AE’s potential, when integrated with machine learning, to provide an effective and reliable framework for early fault detection in complex industrial environments.

Citation

Salah KHENNOUF , ,(2025-12-10), Acoustic Emission Based Bearing Fault Localization using Wavelet Features and Random Forest Classifier,The 2nd International Conference on Advanced Technology in Electronic and Electrical Engineering,جامعة محمد بوضياف-المسيلة

This study presents the design and implementation of controlled by Arabic speech recognition, aimed at improving the autonomy of people with reduced mobility. The system integrates a convolutional neural network (CNN) for voice command classification, combined with a hardware architecture based on Raspberry Pi 4 (voice processing) and Arduino Uno (motor control). Mel frequency cepstral coefficients (MFCC) and short-term Fourier transform (TFCT) are compared for acoustic feature extraction. Experimental results demonstrate an overall accuracy of 98% with MFCC, slightly surpassing TFCT (97%). The system recognizes five Arabic commands (أمام، خلف، يسار، يمين، توقف) with an optimal response time, validating its effectiveness under realistic conditions. This solution opens up prospects for inclusive assistive technologies adapted to Arabic linguistic contexts.

Citation

Salah KHENNOUF , ,(2025-12-10), Development of an Arabic Voice Control System using Convolutional Neural Networks CNN,The 2nd International Conference on Advanced Technology in Electronic and Electrical Engineering,جامعة محمد بوضياف-المسيلة

A_Deep_Learning_Approach_using_ResNet_50_for_Arabic_Sign_Language_Recognition atte.pdf

Citation

ABDELHAFID Benyounes , Mounir BOURAS , ABDELGHAFOUR Herizi , Salah KHENNOUF , FAYSSAL Ouagueni , ,(2025-09-02), A Deep Learning Approach using ResNet-50 for Arabic Sign Language Recognition,ICMS 2025,turkey

Photovoltaic (PV) solar cells are the most commonly used systems for renewable energy generation. However, their efficiency remains relatively low, primarily due to a mismatch between the narrow wavelength range associated with the semiconductor bandgap and the broad spectral distribution of sunlight, which follows a blackbody radiation profile. As a result, PV cells convert light most effectively when the photon energy closely matches the bandgap energy of the material, making their performance highly dependent on the wavelength of incident light. This study aims to address this limitation by exploring how different wavelengths affect the performance of a silicon (Si) solar cell. An experimental setup was designed to measure the power–irradiance (P–Y) characteristics of a Si solar cell (model 307-137) using four colored optical filters -red, blue, yellow, and green- each allowing specific wavelength ranges to pass through. A consistent light source was applied across all tests, and the resulting voltage and current were recorded for each filter. The goal was to observe how varying wavelengths influence the energy conversion process. The experimental results showed valuable insights into the spectral response of silicon-based PV cells and suggest potential strategies for improving overall efficiency through wavelength optimization.

Citation

Salah KHENNOUF , ,(2025-05-06), Boosted Photoconversion Efficiency of Silicon Solar Cells via Spectral Management using Wavelength-Selective Optical Filters,The First National Conference on Renewable Energies and Advanced Electrical Engineering,جامعة محمد بوضياف-المسيلة

AI Serving Homeland Security and Safety

Citation

Salah KHENNOUF , ,(2024-10-29), AI Serving Homeland Security and Safety,The International Conference for AI Serving Homeland Security and Safety,Doha - Qatar

Abstract- Imbalanced Datasets are one of the major challenges in text mining. In order to tackle the issue of imbalanced datasets in the Authorship Attribution (AA) task, particularly when applied to Arabic text data, we proposed a new hybrid approach based on AraVec representation and Synthetic minority oversampling technique (SMOTE). That involves the use of layer of balancing after the embedding representation step in AraVec. This layer is trained to adjust the weight of each sample based on the class distribution, effectively balancing the training process for all classes. The results of the proposed approach have shown significant improvements over the model baseline and demonstrating its effectiveness in addressing the problem of imbalanced datasets in Arabic Authorship Attribution.

Citation

Salah KHENNOUF , ,(2024-09-23), Improving Arabic Authorship Attribution on Imbalanced Dataset Using a Hybrid Approach,The 4th Doctoral Days of Speech Communication And Signal Processing Laboratory,USTHB, Bab Ezzouar, Algiers - Algeria

Authorship Attribution is a research area concerned with the automatic classification of text documents based on their authors. The main objective of this investigation area is to find out who is the author of a given text. This task becomes very tough as far as old text documents are concerned. In this paper, we attempted to broach the Authorship Attribution problem as it applies to old text documents. For this purpose, several experiments are conducted and their results are commented. In order to validate the performances of our system, we constructed a special dataset that we called ''A10P '' (10 Ancient Arabic Philosophers), by quoting texts from the works of 10 ancient Arabic philosophers, where the topic of the different texts is the same. Moreover, the genre of the authors is also the same.

Citation

Salah KHENNOUF , Abderrzak Laib , Halim Sayoud, ,(2022), Performances Evaluation of Automatic Authorship Attribution on Ancient Arabic Documents,International Conference of advanced Technology in Electronic and Electrical Engineering,University of Msila

In this paper, we have proposed a new design, to enhance and simulate a Highly Sensitive Mach-Zehnder Interferometer (MZI) Biochemical sensing platform using a Silicon Rib Waveguide. We considered two different MZI configurations: the first one with an S-bend & Y-junction and the second with an angular Y-junction. We determined the critical cutoff radius and the critical cut-off angle for the S-bend & Y-junction and the angular Yjunction configurations respectively. Based on the analyses of the evanescent field intensity, the mode polarization and cross section dimensions of the Silicon Rib waveguide are optimized using beam propagation method. The critical parameters of the design are calculated to ensure minimal optical losses and a new sensitivity value of 308 dB/RIU with a detection limit of 10-7, which shows the ability of the structure to produce biosensor.

Citation

Salah KHENNOUF , Mounir BOURAS , , (2022), A New Design for Enhancing Highly Sensitive Interferometer Biosensor Using a Silicon Rib Waveguide, Instrumentation Mesure Métrologie, Vol:21, Issue:6, pages:231-236, International Information and Engineering Technology Association

In this research work, we are dealing with an Automatic Speaker Verification problem, which consists on the determination if a person really is the person he/she claims to be, using his/her speech signal characteristics. Therefore, we conducted three series of experiments applied to a subset of Hub4 Broadcast-News database using a Support Vector Machine (SVM) as classifier and the Mel Frequency Spectral Coefficients (MFSC) as speakers’ features. In the first series of experiments, we investigated the effect of the number of features in order to obtain the minimum number that gives a Good Verification Score (GVScore). In the second series of experiments, as there are many types of kernel functions, the appropriate one for speaker verification is investigated. In the last series of experiments, we investigated the GVScore with regard to speaker gender (Male vs. Male, Female vs. Female and Male vs. Female). In our approach, we have used the MFSC as features extraction, which are calculated in both training and testing sessions. The obtained results of the proposed techniques are quite interesting.

Citation

Salah KHENNOUF , SAYOUD Halim, ,(2020), Kernel Function and Dimensionality Reduction Effects on Speaker Discrimination System,The 6th International Conference on Electrical Engineering- ICEE’2020,Istanbul, Turkey

Ce cours de Fiabilité et Maintenance des Systèmes Electroniques a été rédigé, conformément au programme officiel de formation, à l’intention des étudiants qui préparent, un master dans le domaine des Sciences et Technologies, Filière : Electronique, Option : Instrumentation. Il est enseigné en 3ème semestre, à raison d’une heure et demi de cours par semaine est complété par une heure de travaux pratiques. Le contenu du programme proposé par la tutelle est relativement long, l’enseignant doit alors se limiter aux concepts importants et c’est à l’étudiant de fournir un effort supplémentaire pour prendre en charge tous ces concepts. Ce cours, indispensable pour l’étudiant en master électronique, se divise en six chapitres.

Citation

SalahKHENNOUF , ,(2020); Fiabilité et Maintenance des Systèmes Electroniques,University of M'sila,

In this paper, we propose a research work on speaker discrimination using a multi-classifier fusion with focus on feature reduction effects. Speaker discrimination consists in the automatic distinction between two speakers using the vocal characteristics of their speeches. A number of features are extracted using Mel Frequency Spectral Coefficients and then reduced using Relative Speaker Characteristic (RSC) along with the Principal Components Analysis (PCA). Several classification methods are implemented to ensure the discrimination task. Since different classifiers are employed, two fusion algorithms at the decision level, referred to as Weighted Fusion and Fuzzy Fusion, are proposed to boost the classification performances. These algorithms are based on the weighting of the different classifiers outputs. Furthermore, the effects of speaker gender and feature reduction on the speaker discrimination task have been examined too. The evaluation of our approaches was conducted on a subset of Hub-4 Broadcast-News. The experimental results have shown that the speaker discrimination accuracy is improved by 5–15% using the (RSC–PCA) feature reduction. In addition, the proposed fusion methods recorded an improvement of about 10% compared to the individual scores of the classifiers. Finally, we noticed that the gender has an important impact on the discrimination performances.

Citation

Salah KHENNOUF , SAYOUD Halim, , (2018), Speaker discrimination based on fuzzy fusion and feature reduction techniques, International Journal of Speech Technology, Vol:21, Issue:1, pages:51-63, Springer

Authorship attribution is the application of the linguistic study of an anonymous text to identify its actual author. In this paper, we are interested in identifying the author of texts obtained through the transcription of oral discourses. For this purpose, we constructed a special corpus that we called ''SC2T'' (Speech Converted to Text), containing text documents with an average size of 275 words, which are obtained by transcribing oral religious discourses of 14 Arabic contemporary preachers speaking in the same topic. These texts were transcribed manually retaining all the repeated as well as the mispronounced words. Several features and classifiers were employed and evaluated with respect to the Score of Good Authorship Attribution (SGAA) performances. Results are quite interesting and show that the most robust feature in authorship Attribution is the character-Tetragram, which provides a SGAA of 80%.

Citation

Salah KHENNOUF , Hassina HADJADJ, Halim SAYOUD, ,(2017), Automatic Authorship Attribution of Transcribed Texts –Application on Oral Religious Discourses,NTERNATIONAL CONFERENCE ON ELECTRONICS AND NEW TECHNOLOGIES,Univ-M'sila

Photovoltaic (PV) solar energy conversion systems (or solar cells) are the most widely used power systems. However, these devices suffer of very low conversion efficiency. This is due to the wavelength mismatch between the narrow wavelength band associated with the semiconductor energy gap and the broad band of the (blackbody) Emission curve of the Sun [1]. Thus, the photovoltaic conversion is highly wavelength dependant and is most efficient when converting photons of energies close to PV cell band gap energy [2]. In the present research work, we tried to treat this problem, which is related to the optimization of the energy conversion of a Si-solar cell, using different colored filters having different wavelength. For this purpose, we have conducted an experimental work aiming to find out the P-Y characteristics of the solar cell. This experimental work consists of applying an illuminating light source on a Si-solar cell (type 307-137) across 4 colored filters (Red, Blue, Yellow and Green) one by one, each one having a specific wavelength, and measuring each time the resulting voltage and current (power). The obtained results are quite interesting.

Citation

Salah KHENNOUF , Amar GUICHI , ,(2015), Energy conversion optimization of Si-solar cell using different wavelength filters,THE FIRST INTERNATIONAL CONFERENCE ON SOLAR ENERGY (INCOSOLE 2015),University of Bordj Bou Arréridj

Our research work deals with the problem of automatic speaker tracking by camera. Such tracking systems do exist nowadays, but they suffer from a number of mechanical problems. To overcome these problems, we thought of employing a virtual tracking system using a fixed camera that does not require any mechanical part. But, is it possible to track a moving speaker with a fixed camera? If the task is already difficult enough with a mobile camera, how difficult would it be with a fixed camera? Trying to find a solution to the problem, we have proposed and conceived a virtual tracking system, which is able to ensure the required task by using only two cardioid microphones and a classic video camera. In this virtual tracking system, the task of speaker tracking is ensured by the orientation of the region of interest ROI of the camera towards the active speaker; we have called this method the virtual region of interest VROI based technique. Experiments show the good performance of the new virtual technique.

Citation

Salah KHENNOUF , SAYOUD Halim, , (2013), Virtual speaker tracking by camera using a sound source localisation with two microphones, International Journal of Networking and Virtual Organisations, Vol:12, Issue:2, pages:85-110, Inderscience

Purpose The purpose of this paper is two‐fold. First, to deal with the problem of audio speaker localization and second, to deal with the problem of mobile camera control. The task of speaker localization consists of determining the position of the active speaker and the task of camera control consists of orienting a mobile camera towards that active speaker. These steps represent the main task of speaker tracking, which is the global purpose of the research work. Design/methodology/approach In this approach, two‐channel‐based estimation of the speaker position is achieved by comparing the signals received by two cardioids microphones, which are placed the one against the other and separated by a fixed distance. The localization technique presented in this paper is inspired from the human ears, which act as two different sound observation points, enabling humans to estimate the direction of the speaking person with a good precision. Concerning the camera control part, the authors have conceived an automatic system for generating the command signals and controlling the rotation of the mobile camera by a stepper motor. Findings The off‐line experiments of speaker tracking by camera have been done in a small meeting room without echo cancelation. Results show the good performances of the proposed localization methods and a correct tracking by camera. Practical implications This new technique can be used for the automatic supervision of smart rooms. Originality/value The work described in this paper is original, since it uses only two microphones for the speaker localization.

Citation

Salah KHENNOUF , SAYOUD Halim, OUAMOUR Siham, , (2011), Automatic speaker tracking by camera using two-channel-based sound source localization, International Journal of Intelligent Computing and Cybernetics, Vol:4, Issue:1, pages:40-60, Emeral Group Publishing Ltd

This paper presents a system of speaker localization for a purpose of speaker tracking by camera. The authors use the information given by the two microphones, placed in opposition, to determine the position of the active speaker in trying to supervise the audio-visual recording. To achieve the speaker localization task, the authors have proposed and employed two methods, which are called respectively: the filtered correlation method and the energy differential method. The principle of the first method is based on the calculation of the correlation between the two signals collected by the two microphones and a special filtering. The second is based on the computation of the logarithmic energy differential between these two signals. However, when different methods are used simultaneously to make a decision, it is often interesting to use a fusion technique combining those estimations or decisions in order to enhance the system performances. For that purpose, this paper proposes two fusion techniques operating at the decision level which are used to fuse the two estimations into one that should be more precise.

Citation

Salah KHENNOUF , OUAMOUR Siham, SAYOUD Halim, , (2010), Automatic Speaker Localization and Tracking Using a Fusion of the Filtered Correlation with the Energy Differential, International Journal of Mobile Computing and Multimedia Communications, Vol:2, Issue:3, pages:15-33, IGI Global publishing