H. R. Sadegh Mohammadi

Verified email at acecr.ac.ir

Communications
Iranian Research Institute for Electrical Engineering, ACECR



                                    

http://researchid.co/arefeh71
21

Scopus Publications

158

Scholar Citations

7

Scholar h-index

5

Scholar i10-index

Scopus Publications

  • Weighted I-Vector Based Text-Independent Speaker Verification System
    Mohsen Mohammadi and Hamid Reza Sadegh Mohammadi

    ICEE 2019 - 27th Iranian Conference on Electrical Engineering, Pages: 1647-1653, Published: April 2019 IEEE
    Speaker recognition is one of the most common and user-friendly methods for biological signals based people identification. Nowadays, Speaker verification based on factor analysis and i-vector space has a great impact on the performance improvement of these systems. In this paper, a method is proposed for weighting the model and test vectors, which utilizes the statistical characteristics of target training vectors. The effect of the use of weighted vectors on the accuracy of scoring and the performance of the entire speaker verification system was evaluated for Mel-frequency cepstral coefficients (MFCC) and power-normalized cepstral coefficients (PNCC) feature vectors, and two scoring methods, i.e., the cosine distance and probabilistic linear discriminant analysis (PLDA). TIMIT database has been used in the evaluation of the system. The test results indicate that the use of proposed weighted vectors reduces the error rate of the speaker verification system significantly.

  • Modified histogram-based segmentation and adaptive distance tracking of sperm cells image sequences
    Fateme Mostajer Kheirkhah, Hamid Reza Sadegh Mohammadi, and Abdolhossein Shahverdi

    Computer Methods and Programs in Biomedicine, ISSN: 01692607, eISSN: 18727565, Volume: 154, Pages: 173-182, Published: February 2018 Elsevier BV
    Proper recognition and tracking of microscopic sperm cells in video images are vital steps of male infertility diagnosis and treatment. The segmentation and detection of sperms in microscopic image analysis is a complicate process as a result of their small sizes, fast movements, and considerable collisions. Histogram-based thresholding schemes are very popular for this purpose, since they are quite fast and provide almost acceptable results. This paper proposes a combined method for sperm cells detection, which consists of a non-linear pre-processing stage, a histogram-based thresholding algorithm, and a tracking method based on an adaptive distance scheme. The results of conducted experiments verify the superiority of the proposed scheme with incorporated Kittler algorithm compared to the other competitive methods in the majority of cases.

  • Robust features fusion for text independent speaker verification enhancement in noisy environments
    Mohsen Mohammadi and Hamid Reza Sadegh Mohammadi

    2017 25th Iranian Conference on Electrical Engineering, ICEE 2017, Pages: 1863-1868, Published: 19 July 2017 IEEE
    So far, many methods have been proposed for speaker verification which provide good results, but their performances reduce in actual noisy environments. A common approach to partially alleviate this problem is the fusion of several methods. In this paper, four systems based on different speech features, i.e., MFCC, IMFCC, LFCC, and PNCC were combined in score-level to improve verification accuracy under clean and noisy speech conditions. The features pairwise and foursome fusion in a speaker verification system based on speaker modeling through the Gaussian mixture model (GMM) were evaluated. TIMIT and NOISEX92 databases were used to implement as the speech and noise datasets, respectively. The experimental results show that the score-level fusion of different feature vectors enhances the accuracy of speaker verification system and this reduces the equal error rates is in some cases up to 44%.

  • Study of speech features robustness for speaker verification application in noisy environments
    Mohsen Mohammadi and Hamid Reza Sadegh Mohammadi

    2016 8th International Symposium on Telecommunications, IST 2016, Pages: 489-493, Published: 17 March 2017 IEEE
    This paper presents a comparative study and evaluation of the performances of four speech feature vectors, i.e., MFCC, IMFCC, LFCC, and PNCC in a speaker verification system based on speaker modeling through the Gaussian mixture model (GMM) under clean and noisy speech conditions. The TIMIT and NOISEX92 dataset were used in implementing the tests for speech signal and noise, respectively. The evaluation results show that IMFCC and PNCC provide superior performance in the presence of noise. In order to enhance the performance of the system under noisy conditions, the application of spectral subtraction algorithm as a pre-processing stage was investigated. It only improved the performance for the speech signal contaminated with white noise.

  • Histogram non-linear transform for sperm cells image detection enhancement
    F. Mostajer Kheirkhah, H. R. Sadegh Mohammadi, and A. Shahverdi

    2016 8th International Conference on Information and Knowledge Technology, IKT 2016, Pages: 25-30, Published: 7 December 2016 IEEE
    Proper recognition of microscopic sperm cells in video images is an important step in diagnosis and treatment of male infertility. The small sizes of the sperm cells make their segmentation and detection an important stage in the microscopic images analysis. Histogram-based thresholding schemes are one of the common approaches for this purpose. This paper proposes a non-linear amplitude compression transform method applied as a pre-processing stage for histogram-based thresholding algorithms. The results of conducted experiments verify the higher performance of the proposed scheme when used with Kittler method compared to its utilization with the other competitive algorithms in most cases for this application.

  • Joint frame and Gaussian selection for text independent speaker verification
    Rahim Saeidi, Tomi Kinnunen, Hamid Reza Sadegh Mohammadi, Robert Rodman, and Pasi Franti

    ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, ISSN: 15206149, Pages: 4530-4533, Published: 2010 IEEE
    Gaussian selection is a technique applied in the GMM-UBM framework to accelerate score calculation. We have recently introduced a novel Gaussian selection method known as sorted GMM (SGMM). SGMM uses scalar-indexing of the universal background model mean vectors to achieve fast search of the top-scoring Gaussians. In the present work we extend this method by using 2-dimensional indexing, which leads to simultaneous frame and Gaussian selection. Our results on the NIST 2002 speaker recognition evaluation corpus indicate that both the 1- and 2- dimensional SGMMs outperform frame decimation and temporal tracking of top-scoring Gaussians by a wide margin (in terms of Gaussian computations relative to GMM-UBM as baseline).

  • Particle swarm optimization for sorted adapted gaussian mixture models
    R. Saeidi, H.R.S. Mohammadi, T. Ganchev, and R.D. Rodman

    IEEE Transactions on Audio, Speech and Language Processing, ISSN: 15587916, Pages: 344-353, Published: February 2009 Institute of Electrical and Electronics Engineers (IEEE)
    Recently, we introduced the sorted Gaussian mixture models (SGMMs) algorithm providing the means to tradeoff performance for operational speed and thus permitting the speed-up of GMM-based classification schemes. The performance of the SGMM algorithm depends on the proper choice of the sorting function, and the proper adjustment of its parameters. In the present work, we employ particle swarm optimization (PSO) and an appropriate fitness function to find the most advantageous parameters of the sorting function. We evaluate the practical significance of our approach on the text-independent speaker verification task utilizing the NIST 2002 speaker recognition evaluation (SRE) database while following the NIST SRE experimental protocol. The experimental results demonstrate a superior performance of the SGMM algorithm using PSO when compared to the original SGMM. For comprehensiveness we also compared these results with those from a baseline Gaussian mixture model-universal background model (GMM-UBM) system. The experimental results suggest that the performance loss due to speed-up is partially mitigated using PSO-derived weights in a sorted GMM-based scheme.

  • Effects of feature domain normalizations on text independent speaker verification using sorted adapted Gaussian mixture models
    Rahim Saeidi, Hamid Reza Sadegh Mohammadi, Todor Ganchev, and Robert D. Rodman

    Communications in Computer and Information Science, ISSN: 18650929, Volume: 6 CCIS, Pages: 493-500, Published: 2008 Springer Berlin Heidelberg
    In this paper we evaluate sorted Gaussian Mixture Model (GMM) system performance for Text Independent Speaker Verification under the feature domain normalization conditions. Sorted GMM is a speed-up algorithm proposed for GMM based systems. Cepstral Mean Subtraction (CMS) and Dynamic Range Normalization (DRN) are the normalization schemes studied for sorted GMM system purposes. Effectiveness of these normalizations has been proved in speaker recognition systems while their effectiveness on the speed-up of GMM based speaker verification is showed in this study. The baseline system is a universal background model–Gaussian mixture model (UBM-GMM) system and evaluations were performed on the NIST 2002 speaker recognition evaluation database with NIST SRE rules. It is shown that CMS and DRN normalizations enhance both the baseline system and sorted GMM system performances. In other words, the performance loss due to reducing the computational load is mitigated by applying CMS and DRN.

  • Field simulation of a high voltage inductor for series resonant generator
    A. A. Lotfi Neyestanak, M. Jahanbakht, H. R. Sadegh Mohammadi, and A. Graeeli

    Journal of Electromagnetic Waves and Applications, ISSN: 09205071, eISSN: 15693937, Issue: 17-18, Pages: 2391-2398, Published: 1 December 2008 Informa UK Limited
    In this paper a high power inductor has been designed, analyzed, and then fabricated to work with high power capacitive loads in different industrial tests. This inductor has also been used as a part of resonant generators next to isolated transformer, voltage regulator, and low/high power filters. Moreover, the simulation of magnetic field on the proposed inductor has been performed using the ANSYS Software. The inductance measurement of the implemented variable inductor matches with the simulation results.

  • Hierarchical mixture clustering and its application to GMM based text independent speaker identification
    R. Saeidi, H. R. Sadegh Mohammadi, T. Ganchev, and R. D. Rodman

    2008 International Symposium on Telecommunications, IST 2008, Pages: 770-773, Published: 2008 IEEE
    In this paper, we propose a hierarchical mixture clustering method and investigate its application for complexity reduction of a GMM based speaker identification system. We show that by using GMM-HMC one can cluster speakers more accurately than that of a sorted GMM with the same acceleration rate. The system was tested on a universal background model-Gaussian mixture model with KL-divergence as the distance measure. While the proposed systempsilas performance is slightly inferior to the baseline system, its comparatively smaller computational load provides the potential to develop systems with higher performance.

  • Speaker identification performance enhancement using Gaussian mixture model with GMM classification post-processor
    H. R. Sadegh Mohammadi and R. Saeidi

    ICSPC 2007 Proceedings - 2007 IEEE International Conference on Signal Processing and Communications, Pages: 504-507, Published: 2007 IEEE
    In this paper the application of Gaussian mixture model (GMM) classifier is investigated as an efficient post-processing method to enhance the performance of GMM-based speaker identification systems; such as Gaussian mixture model universal background model (GMM-UBM) scheme. The proposed classifier presents outstanding performance while its computational complexity is almost negligible compared to the main GMM system. Moreover, the effects of the model order of GMM classifier is studied using experimental method. Experimental results verify the superior performance of applying GMM post-processor while the proper selection of model order for this GMM has a great impact on the overall performance of the system.

  • Text independent speaker verification using enhanced sorted Gaussian mixture model
    R. Saeidi, T. Ganchev, and H. R. Sadegh Mohammadi

    ICSPC 2007 Proceedings - 2007 IEEE International Conference on Signal Processing and Communications, Pages: 1191-1194, Published: 2007 IEEE
    In this work we study an enhanced sorting function for the recently developed sorted GMM, which is computationally efficient method for implementing the Gaussian mixture model universal background model (GMM-UBM) scheme. The sorted GMM employ partial search and thus has lower computational complexity and relaxed memory requirements when compared to the well-known tree-structured GMM of the same model order. Experimental evaluation of the sorted GMM and its enhanced version was performed on two databases: (1) clean speech in Farsi recorded from TV broadcasts, and (2) telephone quality speech in english (NIST 2002 SRE one-speaker detection data). The enhanced sorting scheme outperformed the original one, primarily for cases where very high acceleration rates were targeted, in scenarios where there was match between training and testing conditions. However, in mismatched train-test conditions the original sorted GMM performed better. Finally, the sorted GMM proved 14 times faster than the baseline system at the cost of only 0.43 increase in equal error rate.

  • Combined inter-frame and intra-frame fast scoring methods for efficient implementation of GMM-based speaker verification systems
    H. R. Sadegh Mohammadi, R. Saeidi, M. R. Rohani, and R. D. Rodman

    ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, ISSN: 15206149, Published: 2007 IEEE
    In this paper a new inter-frame fast scoring scheme is proposed for Gaussian mixture model universal background model (GMM-UBM) speaker verification systems. It is combined with a recently introduced intra-frame efficient scoring method called the sorted Gaussian mixture model (SGMM) classifier which itself uses a sorted UBM known as the sorted background model (SBM). To enhance the performance of the system a GMM identifier is applied as a post-processing block. Experimental results show that the performance of this combined method compares favorably with the baseline GMM-UBM system, while the computational load of the proposed system is greatly less than that of the baseline system.

  • A new segmentation algorithm combined with transient frames power for text independent speaker verification
    R. Saeidi, H. R. Sadegh Mohammadi, R. D. Rodman, and T. Kinnunen

    ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, ISSN: 15206149, Published: 2007 IEEE
    In this paper we propose a new segmentation algorithm called delta MFCC based speech segmentation (DMFCC-SS), with application to speaker recognition systems. We show that DMFCC-SS can separate the regions of speech that result from similar likelihood scores using models such as a Gaussian mixture model (GMM), and can therefore be used to identify the regions of speech between two transitional states in a speech signal. By combining this segmentation algorithm with the discriminative power of transient frames in speaker recognition, we can investigate the tradeoff in speed-up rates that result from DMFCC-SS, with speaker verification equal error rates that result from representatives of each segment. We use a universal background model Gaussian mixture model (UBM-GMM) as a baseline system. The proposed speed-up algorithm, working in the pre-processing stage, performs well while having no computational load compared to the main GMM system. Experimental results show the superior performance of this pre-processing method in comparison with other algorithms working in the pre-processing stage of a UBM-GMM system.

  • Iranian Journal of Electrical and Computer Engineering: Editorial Note
    Iranian Journal of Electrical and Computer Engineering, ISSN: 16820053, Published: December 2006

  • Efficient implementation of GMM based speaker verification using sorted Gaussian mixture model
    European Signal Processing Conference, ISSN: 22195491, Published: 2006

  • An efficient gmm classification post-processing method for structural Gaussian mixture model based speaker verification
    ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, ISSN: 15206149, Published: 2006

  • Iranian Journal of Electrical and Computer Engineering: Editorial Note
    Iranian Journal of Electrical and Computer Engineering, ISSN: 16820053, Published: June 2005

  • Iranian Journal of Electrical and Computer Engineering: Editorial note
    Iranian Journal of Electrical and Computer Engineering, ISSN: 16820053, Published: December 2004


  • Efficient coding of the short-term speech spectrum with two-step vector quantization methods
    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, ISSN: 09168508, Volume: E78-A, Pages: 1178-1185, Published: September 1995

RECENT SCHOLAR PUBLICATIONS

  • Efficient and Robust Segmentation and Tracking of Sperm Cells in Microscopic Image Sequences
    F Mostajer Kheirkhah, HR Sadegh Mohammadi, A Shahverdi
    IET Computer Vision 13 (5), 489-499 2019

  • Weighted I-Vector Based Text-Independent Speaker Verification System
    M Mohammadi, HRS Mohammadi
    2019 27th Iranian Conference on Electrical Engineering (ICEE), 1647-1653 2019

  • Discriminant Analysis Methods Comparison in I-Vector Space for Speaker Verification
    M Mohammadi, HR Sadegh Mohammadi
    The 9th International Symposium on Telecommunications (IST'2018), 166-172 2018

  • Modified Histogram-Based Segmentation and Adaptive Distance Tracking of Sperm Cells Image Sequences
    F Mostajer Kheirkhah, HR Sadegh Mohammadi, A Shahverdi
    Computer Methods and Programs in Biomedicine 154, 173-182 2018

  • Robust Features Fusion for Text Independent Speaker Verification Enhancement in Noisy Environments
    M Mohammadi, HR Sadegh Mohammadi
    25th Iranian Conference on Electrical Engineering, 5 pp. 2017

  • Study of Speech Features Robustness for Speaker Verification Application in Noisy Environments
    M Mohammadi, HR Sadegh Mohammadi
    8th International Symposium on Telecommunications, 5 pp. 2016

  • Histogram Non-Linear Transform for Sperm Cells Image Detection Enhancement
    F Mostajer Kheirkhah, HR Sadegh Mohammadi, A Shahverdi
    Eighth International Conference on Information and Knowledge Technology (IKT 2016

  • Joint frame and Gaussian selection for text independent speaker verification
    R Saeidi, T Kinnunen, HR Sadegh Mohammadi, R Rodman, P Frnti
    2010 IEEE International Conference on Acoustics, Speech and Signal 2010

  • Particle Swarm Optimization for Sorted Adapted Gaussian Mixture Models
    R Saeidi, HR Sadegh Mohammadi, T Ganchev, RD Rodman
    IEEE Transactions on Audio, Speech, and Language Processing 17 (2), 344 - 353 2009

  • Design and Implementation of a Computer System for Partial Discharge Process and Detection
    AAL Neyestanak, HR Sadegh Mohammadi, AE Forooshani, A Graeili
    Electric Power Conference, 2008. EPEC 2008. IEEE Canada, 1-6 2008

  • Hierarchical mixture clustering and its application to GMM based text independent speaker identification
    R Saeidi, HR Sadegh Mohammadi, T Ganchev, RD Rodman
    2008 International Symposium on Telecommunications, 770-773 2008

  • Effects of Feature Domain Normalizations on Text Independent Speaker Verification Using Sorted Adapted Gaussian Mixture Models
    R Saeidi, HR Sadegh Mohammadi, T Ganchev, RD Rodman
    Computer Society of Iran Computer Conference, 493-500 2008

  • Field Simulation of a High Voltage Inductor for Series Resonant Generator
    AA Lotfi Neyestanak, M Jahanbakht, HR Sadegh Mohammadi, A Graeeli
    Journal of Electromagnetic Waves and Applications 22 (17-18), 2391-2398 2008

  • Text Independent Speaker Verification using Enhanced Sorted Gaussian Mixture Model
    R Saeidi, T Ganchev, HR Sadegh Mohammadi
    2007 IEEE International Conference on Signal Processing and Communications 2007

  • Speaker identification performance enhancement using Gaussian mixture model with GMM classification post-processor
    HR Sadegh Mohammadi, R Saeidi
    2007 IEEE International Conference on Signal Processing and Communications 2007

  • Combined inter-frame and intra-frame fast scoring methods for efficient implementation of GMM-based speaker verification systems
    S Mohammadi HR, R Saeidi, MR Rohani, RD Rodman
    2007 IEEE International Conference on Acoustics, Speech and Signal 2007

  • A new segmentation algorithm combined with transient frames power for text independent speaker verification
    R Saeidi, HR Sadegh Mohammadi, RD Rodman, T Kinnunen
    2007 IEEE International Conference on Acoustics, Speech and Signal 2007

  • Efficient implementation of GMM based speaker verification using sorted Gaussian mixture model
    HR Sadegh Mohammadi, R Saeidi
    14th European Signal Processing Conference, 2006, 1-4 2006

  • An efficient GMM classification post-processing method for structural Gaussian mixture model based speaker verification
    R Saeidi, HR Sadegh Mohammadi, MK Amirhosseini
    2006 IEEE International Conference on Acoustics Speech and Signal Processing 2006

  • Adaptation Parameters Effects in GMM Post-Processor for Structural Gaussian Mixture Model Based Text-Independent Speaker Verification
    R Saeidi, HR Sadegh Mohammadi
    14th Iranian Conference on Electrical Engineering, 6 pp. 2006

MOST CITED SCHOLAR PUBLICATIONS

  • Particle Swarm Optimization for Sorted Adapted Gaussian Mixture Models
    R Saeidi, HR Sadegh Mohammadi, T Ganchev, RD Rodman
    IEEE Transactions on Audio, Speech, and Language Processing 17 (2), 344 - 353 2009
    Citations: 31

  • A new segmentation algorithm combined with transient frames power for text independent speaker verification
    R Saeidi, HR Sadegh Mohammadi, RD Rodman, T Kinnunen
    2007 IEEE International Conference on Acoustics, Speech and Signal 2007
    Citations: 17

  • Efficient implementation of GMM based speaker verification using sorted Gaussian mixture model
    HR Sadegh Mohammadi, R Saeidi
    14th European Signal Processing Conference, 2006, 1-4 2006
    Citations: 17

  • Low cost vector quantization methods for spectral coding in low rate speech coders
    HR Sadegh Mohammadi, WH Holmes
    1995 International Conference on Acoustics, Speech, and Signal Processing 1 1995
    Citations: 15

  • Speaker identification performance enhancement using Gaussian mixture model with GMM classification post-processor
    HR Sadegh Mohammadi, R Saeidi
    2007 IEEE International Conference on Signal Processing and Communications 2007
    Citations: 10

  • An efficient GMM classification post-processing method for structural Gaussian mixture model based speaker verification
    R Saeidi, HR Sadegh Mohammadi, MK Amirhosseini
    2006 IEEE International Conference on Acoustics Speech and Signal Processing 2006
    Citations: 8

  • Study of model parameters effects in adapted Gaussian mixture models based text independent speaker verification
    R Saeidi, HR Sadegh Mohammadi, MK Amirhosseini
    Proc. International Symp. of Telecommunications, IST 2005 1, 387-392 2005
    Citations: 8

  • Joint frame and Gaussian selection for text independent speaker verification
    R Saeidi, T Kinnunen, HR Sadegh Mohammadi, R Rodman, P Frnti
    2010 IEEE International Conference on Acoustics, Speech and Signal 2010
    Citations: 7

  • Combined inter-frame and intra-frame fast scoring methods for efficient implementation of GMM-based speaker verification systems
    S Mohammadi HR, R Saeidi, MR Rohani, RD Rodman
    2007 IEEE International Conference on Acoustics, Speech and Signal 2007
    Citations: 7

  • Fine-coarse split vector quantization: an efficient method for spectral coding
    HR Sadegh Mohammadi, WH Holmes
    Fifth Australian International Conference on Speech Science and Technology 1 1994
    Citations: 6

  • Robust Features Fusion for Text Independent Speaker Verification Enhancement in Noisy Environments
    M Mohammadi, HR Sadegh Mohammadi
    25th Iranian Conference on Electrical Engineering, 5 pp. 2017
    Citations: 5

  • Histogram Non-Linear Transform for Sperm Cells Image Detection Enhancement
    F Mostajer Kheirkhah, HR Sadegh Mohammadi, A Shahverdi
    Eighth International Conference on Information and Knowledge Technology (IKT 2016
    Citations: 4

  • Hierarchical mixture clustering and its application to GMM based text independent speaker identification
    R Saeidi, HR Sadegh Mohammadi, T Ganchev, RD Rodman
    2008 International Symposium on Telecommunications, 770-773 2008
    Citations: 4

  • Modified Histogram-Based Segmentation and Adaptive Distance Tracking of Sperm Cells Image Sequences
    F Mostajer Kheirkhah, HR Sadegh Mohammadi, A Shahverdi
    Computer Methods and Programs in Biomedicine 154, 173-182 2018
    Citations: 3

  • Efficient GMM-UBM system in text independent speaker verification using structural Gaussian mixture models,''
    R Saeidi, HR Sadegh Mohammadi, MK Amirhosseini
    Proc. International Symp. of Telecommunications, IST2005 1, 39-44 2005
    Citations: 3

  • Efficient and Robust Segmentation and Tracking of Sperm Cells in Microscopic Image Sequences
    F Mostajer Kheirkhah, HR Sadegh Mohammadi, A Shahverdi
    IET Computer Vision 13 (5), 489-499 2019
    Citations: 2

  • Design and Implementation of a Computer System for Partial Discharge Process and Detection
    AAL Neyestanak, HR Sadegh Mohammadi, AE Forooshani, A Graeili
    Electric Power Conference, 2008. EPEC 2008. IEEE Canada, 1-6 2008
    Citations: 2

  • Application of sorted codebook vector quantization to spectral coding of speech
    HR Sadegh Mohammadi, WH Holmes
    Proceedings of GLOBECOM'95 3, 1595-1598 1995
    Citations: 2

  • an editor's notes, sixth note: Derivative Plagiarism
    HR Sadegh Mohammadi

    Citations: 2

  • an editor's notes, sixth note: Translated Plagiarism
    HR Sadegh Mohammadi

    Citations: 2