International journal of engineering research and technology, May 13, 2015
In this paper, we present a new robust algorithm involving the pre-processing and the extraction ... more In this paper, we present a new robust algorithm involving the pre-processing and the extraction of pitch pattern. This method combine the autocorrelation function (ACF) and the AMDF (Average Magnitude Difference Function) to take the advantage of their complementary nature. The falling trends are eliminated by an alignment technique. ACF and AMDF are multiplied and added for several pass band filters to obtain a correct pitch. We present the implementation and the basic experiments and discussions for the proposed algorithm.
International Journal of Advanced Computer Science and Applications, 2016
The diagnosis of voice diseases through the invasive medical techniques is an efficient way but i... more The diagnosis of voice diseases through the invasive medical techniques is an efficient way but it is often uncomfortable for patients, therefore, the automatic speech recognition methods have attracted more and more interest recent years and have known a real success in the identification of voice impairments. In this context, this paper proposes a reliable algorithm for voice disorders identification based on two classification algorithms; the Artificial Neural Networks (ANN) and the Support Vector Machine (SVM). The feature extraction task is performed by the Mel Frequency Cepstral Coefficients (MFCC) and their first and second derivatives. In addition, the Linear Discriminant Analysis (LDA) is proposed as feature selection procedure in order to enhance the discriminative ability of the algorithm and minimize its complexity. The proposed voice disorders identification system is evaluated based on a widespread performance measures such as the accuracy, sensitivity, specificity, precision and Area Under Curve (AUC).
In this paper, we propose a novel digital watermarking scheme in DCT domain based fuzzy inference... more In this paper, we propose a novel digital watermarking scheme in DCT domain based fuzzy inference system and the human visual system to adapt the embedding strength of different blocks. Firstly, the original image is divided into some 8×8 blocks, and then fuzzy inference system according to different textural features and luminance of each block decide adaptively different embedding strengths. The watermark detection adopts correlation technology. Experimental results show that the proposed scheme has good imperceptibility and high robustness to common image processing operators.
Many advances have been made in recent years in the development of hearing and cochlear implants.... more Many advances have been made in recent years in the development of hearing and cochlear implants. These use acoustic and electrical stimulation technologies to improve speech intelligibility for the hearing impaired. However, for cochlear prostheses, the results are not very promising and vary from one patient to another. Certain technical and sometimes physiological problems have limited the expected performances of these devices, especially for children and the elderly. These problems include cochlear malformation and ossification of the auditory channels. This led us to reduce the number of electrodes in order to allow quality deep insertion while preserving the low-frequency acoustic bands of the operated patient.
This paper presents a simulation model of the electric part of a grid connected photovoltaic gene... more This paper presents a simulation model of the electric part of a grid connected photovoltaic generator. The model contains a detailed representation of the main components of the system that are the solar array, boost converter and the grid side inverter. A proper control of the DC/DC converter is developed in order to extract the maximum amount of from the
Artificial Neural Networks have demonstrated best effectiveness and excellent scheduling capabili... more Artificial Neural Networks have demonstrated best effectiveness and excellent scheduling capabilities in realizing many purposes like recognition, clustering, classification, management and even prediction. For this reason, we have used RBF based Artificial NN for the dynamic forecasting of load and Photovoltaic production using many operations like forecasting, training and validation of the data accuracy. For the validation, the Mean Absolute Percent Error is calculated in function of the most three relevant input parameters, which are previous load and Photovoltaic production measurements, seasonability and temperature or solar radiation data. This work has used real-time measurements of load and Photovoltaic production for their comparison with the predicted load data using RBFNN algorithms for the calculation of MAE and MAPE, to deduce the performance of forecasting algorithms including the accuracy of the forecasted data. This research paper has treated 2 goals. The first is the short-term energy and Photovoltaic production forecasting including training operations. The 2nd goal is the calculation of Mean Absolute Error and Mean Absolute Percent Error via the comparison between the forecasted data and real-time measurements to evaluate the reliability of forecasted data and the performance of the forecasting algorithms. By this way, the dynamic prediction algorithms were implemented, the predicted data were compared to the same time-series measurements and forecasted energy MAPE was calculated.
Modeling and Simulation of Renewable Generation System: Tunisia Grid Connected PV System Case Study
Smart innovation, systems and technologies, 2019
This paper seeks to evaluate and study Tunisia Grid-Connected system (PV/Wind Turbine), to improv... more This paper seeks to evaluate and study Tunisia Grid-Connected system (PV/Wind Turbine), to improve the electricity production without interruption using renewable energy during daily as well as seasonally periods. In this vein, in order to manage and control the dynamic power stability, two modes have been treated, whether with or without integration of photovoltaics. To distinguish the variations between the two modes, the integrations of Renewable energy will be between 15% and 30%. To perform the correct system operations and to meet load requirements during the peak periods. Considering the impact of included modes and the Renewable energy source integrated into the grid, an accurate fault current characteristic analyzes have been treated. A novel protection scheme using PSSE simulation environment obtains the results and observations is then proposed. The obtained results proven that the loss of the generators have an undesirable effect on stability.
Optimization of MLP Using Genetic Algorithms Applied to Arabic Speech Recognition
International Review on Computers and Software, 2013
This paper presents a novel system for Arabic speech recognition of Arabic isolated words with mo... more This paper presents a novel system for Arabic speech recognition of Arabic isolated words with mono-locutor and a small vocabulary. We have used a database consisting of eleven isolated Arabic words each of them was repeated twenty five times by the same -locutor. Mel Frequency Cepstral Coefficient (MFCC) and Bionic Wavelet Transform (BWT) are used for feature extraction from each recorded word. The obtained coefficients were then concatenated to construct one input node of a Multi-Layer Perceptual (MLP) used for features classification and recognition. We describe in this paper the use of Genetic Algorithm (GA) for optimizing the topology of each Multi-Layer Perceptron (MLP). So, the GA is utilized to find the optimal number of neurons in input layer and in hidden layer, the training epochs and the learning goal of network. From the results, it was observed that the integration of the GA with feed forward network can improve classification rate to 100%
DSP Real-Time Implementation of DOST Algorithm Used for Speech Enhancement
Smart innovation, systems and technologies, Aug 2, 2019
The real-time implementation of speech enhancement is a vital tool destined to ameliorate the spe... more The real-time implementation of speech enhancement is a vital tool destined to ameliorate the speech quality and intelligibility for auditors. In this paper, a speech denoising hardware implementation is developed in order to be used in recognition, synthesis, and coding applications. So, we propose a real-time implementation of speech enhancement approach for single channel in a noisy environment on the basis of Discrete Orthonormal Stockwell Transform (DOST) at the aim to ameliorate the speech quality and intelligibility. The speech enhancement system was tested on DSP TMS320C6416 processor and the obtained results have shown that it has met the real-time requirements in terms of memory consumption (Ko) and number of cycles (MCPS). For a subjective criterion, we have used the Mean Opinion Score (MOS) to evaluate the perceptual quality.
International Journal of Advanced Computer Science and Applications, 2018
Massive capacity and connectivity are the main boundaries towards standing the Internet of Everyt... more Massive capacity and connectivity are the main boundaries towards standing the Internet of Everything (IoE) basis and defining modern wireless generation requirements. These needs cannot be achieved by already deployed phased array antenna in terms of distributed and oriented geometry, dimensions and design. We propose in the present paper an innovating massive multiple input multiple output (MIMO) spherical array network aiming to draw a new three-dimensional configuration to enhance the beam steering, improve bandwidth, total capacity and the scan flexibility. Resolved issues in concordance with 5G requirements are adaptive massive MIMO by using millimeter-wave antenna arrays, small cell design and definition of recommended operational frequency considering the International Telecommunication Union (ITU) norms and directives. The new geometric forms of spherical smart antenna could easily scan all 3D space, ensure higher capacity and reach tens of Giga bit per second (Gbps) value besides eradicating energy wastage aspect of Beam Division Multiple Access (BDMA) in base stations. Mathematical design is detailed and performed simulation results are presented using MATLAB software Tool.
Smart Grid (SG) is the intelligent electrical grid based on information and communication technol... more Smart Grid (SG) is the intelligent electrical grid based on information and communication technologies (ICT) and wireless sensor networks for the exchange of data and energy flows. The main challenges of the SG are the smart metering system(SMS),. The main goal of this research paper is the design and the implementation of a smart metering model devoted to the Tunisian conventional grid using the advanced metering infrastructure (AMI) to enable the intelligence of the Tunisian power grid. To achieve this goal, we have developed a web portal for the Tunisian electrical data company to acquire the realtime load use according to the previous load data measurement and the solar radiation prediction without resorting to the conventional meters for the electrical data reading. The implemented web portal for Tunisian electrical grid has predicted the daily and monthly energy consumption and has sent warning notifications to inform subscribers about the peak power period and to present the overall state of power grid. The used development environment for the smart metering implementation is Software Development kit (SDK) for Android and the obtained results are acquired by using the Am Chart of SDK for Android, the obtained curves are generated by both SDK for Android and Excel software.
Engineering, Technology & Applied Science Research
The development of a real-time automatic speech recognition system (ASR) better adapted to enviro... more The development of a real-time automatic speech recognition system (ASR) better adapted to environmental variabilities, such as noisy surroundings, speaker variations and accents has become a high priority. Robustness is required, and it can be performed at the feature extraction stage which avoids the need for other pre-processing steps. In this paper, a new robust feature extraction method for real-time ASR system is presented. A combination of Mel-frequency cepstral coefficients (MFCC) and discrete wavelet transform (DWT) is proposed. This hybrid system can conserve more extracted speech features which tend to be invariant to noise. The main idea is to extract MFCC features by denoising the obtained coefficients in the wavelet domain by using a median filter (MF). The proposed system has been implemented on Raspberry Pi 3 which is a suitable platform for real-time requirements. The experiments showed a high recognition rate (100%) in clean environment and satisfying results (rang...
International journal of engineering research and technology, May 13, 2015
In this paper, we present a new robust algorithm involving the pre-processing and the extraction ... more In this paper, we present a new robust algorithm involving the pre-processing and the extraction of pitch pattern. This method combine the autocorrelation function (ACF) and the AMDF (Average Magnitude Difference Function) to take the advantage of their complementary nature. The falling trends are eliminated by an alignment technique. ACF and AMDF are multiplied and added for several pass band filters to obtain a correct pitch. We present the implementation and the basic experiments and discussions for the proposed algorithm.
International Journal of Advanced Computer Science and Applications, 2016
The diagnosis of voice diseases through the invasive medical techniques is an efficient way but i... more The diagnosis of voice diseases through the invasive medical techniques is an efficient way but it is often uncomfortable for patients, therefore, the automatic speech recognition methods have attracted more and more interest recent years and have known a real success in the identification of voice impairments. In this context, this paper proposes a reliable algorithm for voice disorders identification based on two classification algorithms; the Artificial Neural Networks (ANN) and the Support Vector Machine (SVM). The feature extraction task is performed by the Mel Frequency Cepstral Coefficients (MFCC) and their first and second derivatives. In addition, the Linear Discriminant Analysis (LDA) is proposed as feature selection procedure in order to enhance the discriminative ability of the algorithm and minimize its complexity. The proposed voice disorders identification system is evaluated based on a widespread performance measures such as the accuracy, sensitivity, specificity, precision and Area Under Curve (AUC).
In this paper, we propose a novel digital watermarking scheme in DCT domain based fuzzy inference... more In this paper, we propose a novel digital watermarking scheme in DCT domain based fuzzy inference system and the human visual system to adapt the embedding strength of different blocks. Firstly, the original image is divided into some 8×8 blocks, and then fuzzy inference system according to different textural features and luminance of each block decide adaptively different embedding strengths. The watermark detection adopts correlation technology. Experimental results show that the proposed scheme has good imperceptibility and high robustness to common image processing operators.
Many advances have been made in recent years in the development of hearing and cochlear implants.... more Many advances have been made in recent years in the development of hearing and cochlear implants. These use acoustic and electrical stimulation technologies to improve speech intelligibility for the hearing impaired. However, for cochlear prostheses, the results are not very promising and vary from one patient to another. Certain technical and sometimes physiological problems have limited the expected performances of these devices, especially for children and the elderly. These problems include cochlear malformation and ossification of the auditory channels. This led us to reduce the number of electrodes in order to allow quality deep insertion while preserving the low-frequency acoustic bands of the operated patient.
This paper presents a simulation model of the electric part of a grid connected photovoltaic gene... more This paper presents a simulation model of the electric part of a grid connected photovoltaic generator. The model contains a detailed representation of the main components of the system that are the solar array, boost converter and the grid side inverter. A proper control of the DC/DC converter is developed in order to extract the maximum amount of from the
Artificial Neural Networks have demonstrated best effectiveness and excellent scheduling capabili... more Artificial Neural Networks have demonstrated best effectiveness and excellent scheduling capabilities in realizing many purposes like recognition, clustering, classification, management and even prediction. For this reason, we have used RBF based Artificial NN for the dynamic forecasting of load and Photovoltaic production using many operations like forecasting, training and validation of the data accuracy. For the validation, the Mean Absolute Percent Error is calculated in function of the most three relevant input parameters, which are previous load and Photovoltaic production measurements, seasonability and temperature or solar radiation data. This work has used real-time measurements of load and Photovoltaic production for their comparison with the predicted load data using RBFNN algorithms for the calculation of MAE and MAPE, to deduce the performance of forecasting algorithms including the accuracy of the forecasted data. This research paper has treated 2 goals. The first is the short-term energy and Photovoltaic production forecasting including training operations. The 2nd goal is the calculation of Mean Absolute Error and Mean Absolute Percent Error via the comparison between the forecasted data and real-time measurements to evaluate the reliability of forecasted data and the performance of the forecasting algorithms. By this way, the dynamic prediction algorithms were implemented, the predicted data were compared to the same time-series measurements and forecasted energy MAPE was calculated.
Modeling and Simulation of Renewable Generation System: Tunisia Grid Connected PV System Case Study
Smart innovation, systems and technologies, 2019
This paper seeks to evaluate and study Tunisia Grid-Connected system (PV/Wind Turbine), to improv... more This paper seeks to evaluate and study Tunisia Grid-Connected system (PV/Wind Turbine), to improve the electricity production without interruption using renewable energy during daily as well as seasonally periods. In this vein, in order to manage and control the dynamic power stability, two modes have been treated, whether with or without integration of photovoltaics. To distinguish the variations between the two modes, the integrations of Renewable energy will be between 15% and 30%. To perform the correct system operations and to meet load requirements during the peak periods. Considering the impact of included modes and the Renewable energy source integrated into the grid, an accurate fault current characteristic analyzes have been treated. A novel protection scheme using PSSE simulation environment obtains the results and observations is then proposed. The obtained results proven that the loss of the generators have an undesirable effect on stability.
Optimization of MLP Using Genetic Algorithms Applied to Arabic Speech Recognition
International Review on Computers and Software, 2013
This paper presents a novel system for Arabic speech recognition of Arabic isolated words with mo... more This paper presents a novel system for Arabic speech recognition of Arabic isolated words with mono-locutor and a small vocabulary. We have used a database consisting of eleven isolated Arabic words each of them was repeated twenty five times by the same -locutor. Mel Frequency Cepstral Coefficient (MFCC) and Bionic Wavelet Transform (BWT) are used for feature extraction from each recorded word. The obtained coefficients were then concatenated to construct one input node of a Multi-Layer Perceptual (MLP) used for features classification and recognition. We describe in this paper the use of Genetic Algorithm (GA) for optimizing the topology of each Multi-Layer Perceptron (MLP). So, the GA is utilized to find the optimal number of neurons in input layer and in hidden layer, the training epochs and the learning goal of network. From the results, it was observed that the integration of the GA with feed forward network can improve classification rate to 100%
DSP Real-Time Implementation of DOST Algorithm Used for Speech Enhancement
Smart innovation, systems and technologies, Aug 2, 2019
The real-time implementation of speech enhancement is a vital tool destined to ameliorate the spe... more The real-time implementation of speech enhancement is a vital tool destined to ameliorate the speech quality and intelligibility for auditors. In this paper, a speech denoising hardware implementation is developed in order to be used in recognition, synthesis, and coding applications. So, we propose a real-time implementation of speech enhancement approach for single channel in a noisy environment on the basis of Discrete Orthonormal Stockwell Transform (DOST) at the aim to ameliorate the speech quality and intelligibility. The speech enhancement system was tested on DSP TMS320C6416 processor and the obtained results have shown that it has met the real-time requirements in terms of memory consumption (Ko) and number of cycles (MCPS). For a subjective criterion, we have used the Mean Opinion Score (MOS) to evaluate the perceptual quality.
International Journal of Advanced Computer Science and Applications, 2018
Massive capacity and connectivity are the main boundaries towards standing the Internet of Everyt... more Massive capacity and connectivity are the main boundaries towards standing the Internet of Everything (IoE) basis and defining modern wireless generation requirements. These needs cannot be achieved by already deployed phased array antenna in terms of distributed and oriented geometry, dimensions and design. We propose in the present paper an innovating massive multiple input multiple output (MIMO) spherical array network aiming to draw a new three-dimensional configuration to enhance the beam steering, improve bandwidth, total capacity and the scan flexibility. Resolved issues in concordance with 5G requirements are adaptive massive MIMO by using millimeter-wave antenna arrays, small cell design and definition of recommended operational frequency considering the International Telecommunication Union (ITU) norms and directives. The new geometric forms of spherical smart antenna could easily scan all 3D space, ensure higher capacity and reach tens of Giga bit per second (Gbps) value besides eradicating energy wastage aspect of Beam Division Multiple Access (BDMA) in base stations. Mathematical design is detailed and performed simulation results are presented using MATLAB software Tool.
Smart Grid (SG) is the intelligent electrical grid based on information and communication technol... more Smart Grid (SG) is the intelligent electrical grid based on information and communication technologies (ICT) and wireless sensor networks for the exchange of data and energy flows. The main challenges of the SG are the smart metering system(SMS),. The main goal of this research paper is the design and the implementation of a smart metering model devoted to the Tunisian conventional grid using the advanced metering infrastructure (AMI) to enable the intelligence of the Tunisian power grid. To achieve this goal, we have developed a web portal for the Tunisian electrical data company to acquire the realtime load use according to the previous load data measurement and the solar radiation prediction without resorting to the conventional meters for the electrical data reading. The implemented web portal for Tunisian electrical grid has predicted the daily and monthly energy consumption and has sent warning notifications to inform subscribers about the peak power period and to present the overall state of power grid. The used development environment for the smart metering implementation is Software Development kit (SDK) for Android and the obtained results are acquired by using the Am Chart of SDK for Android, the obtained curves are generated by both SDK for Android and Excel software.
Engineering, Technology & Applied Science Research
The development of a real-time automatic speech recognition system (ASR) better adapted to enviro... more The development of a real-time automatic speech recognition system (ASR) better adapted to environmental variabilities, such as noisy surroundings, speaker variations and accents has become a high priority. Robustness is required, and it can be performed at the feature extraction stage which avoids the need for other pre-processing steps. In this paper, a new robust feature extraction method for real-time ASR system is presented. A combination of Mel-frequency cepstral coefficients (MFCC) and discrete wavelet transform (DWT) is proposed. This hybrid system can conserve more extracted speech features which tend to be invariant to noise. The main idea is to extract MFCC features by denoising the obtained coefficients in the wavelet domain by using a median filter (MF). The proposed system has been implemented on Raspberry Pi 3 which is a suitable platform for real-time requirements. The experiments showed a high recognition rate (100%) in clean environment and satisfying results (rang...
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