Manjutha M

@avinuty.ac.in

Researcher, Department of Computer Science
Avinashilingam Institute for Home Science and Higher Education for Women

Manjutha M


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https://researchid.co/manjutha

EDUCATION

Phd in Computer Science graduated during January 2023

RESEARCH INTERESTS

Speech and Signal Processing and Computational Intelligence
7

Scopus Publications

41

Scholar Citations

4

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • Acoustic analysis of formant frequency variation in tamil stuttered speech
    Manjutha M
    Journal of Advanced Research in Dynamical and Control Systems, 2020
  • Analysis on regularity of speech energy based on optimal thresholding for tamil stuttering dataset
    M Manjutha, P Subashini, M Krishnaveni
    5th IEEE International Smart Cities Conference Isc2 2019, 2019
    All over the world millions of people were affected by speech disorders in which one of the significant speech disorders is stuttering. Over the past two decade immense number of research is going on in the field of fluency disorder, and still it is necessary to enhance the analysis of stuttering disorder regional-wise. The speech signal tempo will vary with each individual where the specific fluctuation in the velocity of stutter speech is typical and it is due to the intervals in the speech rate which has a significant difference in normal stuttered speech. In this paper, Regularity of Speech Energy (RSE) was analyzed as normal, moderate and severe through Tamil speaking stuttered dataset. The analysis was done based on the energy threshold obtained during the irregular release of energy which is henceforth analyzed using optimal thresholding based on Particle Swam optimization (PSO) and Synergistic Fibroblast optimization (SFO) techniques. In order to evaluate the experimental analysis on RSE, statistical measures such as mean, standard deviation, Mean Square Error (MSE) and Root Mean Square Error (RMSE) were calculated. The experimental results of analysis on RSE have proved that stuttered speaker’s signal releases low energy when compared to the normal speaker where the optimal threshold energy enhances the detection of hidden speech energy.
  • An optimized cepstral feature selection method for dysfluencies classification using Tamil speech dataset
    M Manjutha, P Subashini, M Krishnaveni, V Narmadha
    5th IEEE International Smart Cities Conference Isc2 2019, 2019
    Speech is the most important and indispensable mode of communication between humans. In communication, the continuous flow of speech gets affected due to the interruption of emotional, panic and psychological factors that cause syllable or word repetition, prolongation and interjection. Speech dysfluency is a primary challenge for speech pathologist to isolate the normal speech from the stuttered speech. The primary objective of this paper is to propose a novel approach through optimized cepstral features selection that improves the classifiers accuracy. In this paper, Particle Swarm Optimization (PSO) and Synergistic Fibroblast Optimization (SFO) were introduced to select optimal features from conventional MFCC (Mel-Frequency Cepstrum Coefficients). The optimized cepstral features from PSO and SFO of pre-processed Tamil speech data is used to discriminate among different categories of speech signals like Normal, Moderate and Sever stutter through machine learning classification methods such as Support Vector Machine (SVM) and Naive Bayes (NB). From the experimental results, the optimal selection of cepstral features using SFO algorithm has achieved high accuracy of 96.08% employed with NB which outperforms well to the feature selection of PSO and classical MFCC. The evaluation of the proposed methodology is done by using performance metrics like sensitivity, specificity, precision, f-score and accuracy.
  • Vocal tone analysis for identification of stuttering levels based on Tamil syllable
    Manjutha Manavalan, , Dr. Parthasarathy Subashini, Dr. M. Krishnaveni, , and
    International Journal of Recent Technology and Engineering, 2019
    Speech is the most unique feature of humans and it is the basic mode of verbal communication. Among all, a few people face hurdles in producing normal speech because of various types of speech disorders. Stuttering is one of the disorder types mainly characterized by repetition of syllables or words and involuntary interruption during the speech. One of the unsolved problems in the realm of fluency disorder is the level identification, based upon the patient’s utterance before and after the speech therapy. The main objective of the paper is to perform analysis of vocal tone to identify the major differences between a normal, moderate and severely stuttered speech, particularly for the Tamil spoken language. The stutter speech vocal tone analysis involves envelope detection based on Hilbert transform has been computed from the input of normal and stuttered speech waves in which by applying normalization to the spectrum and cepstrum of the obtained signal considering only Tamil syllable as input. The experimental outcomes are given as subjective evaluation in three categories of speech signals which results people affected by severe stuttering having low vocal tone than moderate and normal stuttering speech.
  • An optimal speech recognition module for patient's voice monitoring system in smart healthcare applications
    M Krishnaveni, P Subashini, J Gracy, M Manjutha
    3rd Renewable Energies Power Systems and Green Inclusive Economy Reps and Gie 2018, 2018
    During recent years, health care domain has rapidly developed in which patients and medical resources are directly connected with the smart way that enables Smart Health Care. The growth in design and development of a speech automated system will provide a life assistant service in smart health care environment. In automating the speech system, speech recognition is one of the basic steps to understand the human recognition and their behaviors. These speech recognition systems will be very much accessible for speakers who suffer from dysarthria, a neurological disability that damages the control of motor speech articulators. In this paper, the main objective is to develop an efficient speech recognition module based on the Voice Input Voice Output Communication Aid (VIVOCA) architecture that can device a support aid to the people with DYSARTHRIA. Totally there are seven features extracted from each noise eliminated real time bilingual isolated word speech signal data uttered by a speaker both in Tamil and English languages. Vector Quantization based Genetic Algorithm codebook is created for the recognition modeling. Optimization of Hidden Markov Model (HMM) is done based on Particle Swarm Optimization (PSO) method to improve the recognition accuracy compared to the conventional HMM and also experiment results of the proposed module shows 95% of accuracy. The proposed module will be very much useful for developing a speech recognition system that facilitates the patients and persons with special needs for communication. The proposed module is also evaluated for its complexity which will be therefore efficient for low consumption of energy.
  • Survey on nature inspired algorithm for smart city applications
    T T Dhivyaprabha, M Manjutha, P Subashini
    ACM International Conference Proceeding Series, 2017
    Nature Inspired Computing (NIC) paradigms, namely, swarm intelligence, evolutionary computation and computational intelligence techniques are widely applied to develop versatile and adaptable systems and create computational methods that can assist human to resolve real world complex problems. It can be achieved by transferring knowledge from natural systems to engineering systems. The objective of this paper is to analyze the recent trends and advancement in the application of metaheuristic algorithms to solve various domains, especially, denoising, edge detection and classification problem. This paper provides a comprehensive list of global optimization algorithms that can be applied to develop innovative system and soft computing applications integrates with computational intelligence techniques. Several fitness functions and parameters implemented in the evaluation of global optimization algorithm to find global optimum for solving diverse applications are thoroughly investigated. The implications for the selection of fitness function to solve specific optimization problems and applications are also discussed.
  • Optimized boundary detection algorithm for postal signs recognition system using variant based Particle Swarm intelligence
    P Subashini, M Krishnaveni, M Manjutha
    2016 International Conference on Computation System and Information Technology for Sustainable Solutions Csitss 2016, 2016
    Sign Language is the only mode of communication for deaf and dumb people to convey their messages. Many difficulties are faced by the hearing impaired people when they come across certain areas like Banking, Hospital and Post Office. Especially, there is no proper communication aid available in post offices to support disabled people. From available literature, it is understood that computational methods have been existing in the area of sign language recognition for hearing impaired people. These recognition system acts as an interpreter to accomplish the conversion of sign language into text or voice. This paper proposes an efficient object tracking method, that improves the performance of the video recognition system, by introducing Variant based Particle Swarm Optimization (VPSO) technique in Kalman Filter (KF) through postal video signs. The experimental results prove that VPSO based Efficient Kalman Filter (EKF) provides results better than a traditional KF.

RECENT SCHOLAR PUBLICATIONS

  • Analysis of Tamil Stuttered Speech Using Computational Intelligence
    M Manjutha
    Avinashilingam University , 2022
    2022.0
  • Statistical Model-Based Tamil Stuttered Speech Segmentation Using Voice Activity Detection
    M Manjutha, P Subashini
    Journal of Positive School Psychology 6 (8), 1461-1473 , 2022
    2022.0
  • Soil Nutrient Mining: A Hand-Held Device For On-Farm Soil Analysis And Crop Fertility Prediction
    S Sheela, M Madheslu, M Manjutha
    International Journal of Life Science and Pharma Research 12 (22), 110-115 , 2022
    2022.0
  • Scalable And Secure Sharing of Personal Health Records In Cloud Computing Using Attribute-Based Encryption
    Manjutha M, Arun Kumar K, Subha Sri V, Shree Dharshana D
    International Journal of Life Science and Pharma Research 12 (20), 80-91 , 2022
    2022.0
  • Survey on optimization algorithms in speech processing
    SP Manjutha, M.
    International Journal of Health Sciences 6 (S5), 2997-3017 , 2022
    2022.0
    Citations: 1
  • Cauliflower Disease Identification Using Image Segmentation Based on PSO K-Means Clustering
    SS Manjutha M
    International Journal of Life Science and Pharma Research 12 (22), 26-32 , 2022
    2022.0
  • An Optimized Cepstral Feature Selection method for Dysfluencies Classification using Tamil Speech Dataset
    M Manjutha, P Subashini, M Krishnaveni, V Narmadha
    2019 IEEE International Smart Cities Conference (ISC2), 671-677 , 2019
    2019.0
    Citations: 10
  • Analysis on Regularity of Speech Energy based on Optimal Thresholding for Tamil Stuttering Dataset
    M Manjutha, P Subashini, M Krishnaveni
    2019 IEEE International Smart Cities Conference (ISC2), 143-149 , 2019
    2019.0
  • Vocal Tone Analysis for Identification of Stuttering Levels based on Tamil Syllable
    MK M. Manjutha, P. Subashini
    International Journal of Recent Technology and Engineering (IJRTE) 8 (2 … , 2019
    2019.0
  • An Optimal Speech Recognition Module for Patient's Voice Monitoring System in Smart Healthcare Applications
    M Krishnaveni, P Subashini, J Gracy, M Manjutha
    2018 Renewable Energies, Power Systems & Green Inclusive Economy (REPS-GIE), 1-6 , 2018
    2018.0
    Citations: 4
  • Survey on nature inspired algorithm for smart city applications
    TT Dhivyaprabha, M Manjutha, P Subashini
    Proceedings of the Mediterranean Symposium on Smart City Application, 1-13 , 2017
    2017.0
    Citations: 4
  • Particle Swarm Optimization based Voice Activity Detection for Stuttered Tamil Speech
    Manjutha, Subashini
    International Journal of Computer Engineering and Applications (IJCEA) 11, 1-14 , 2017
    2017.0
    Citations: 2
  • Automated Speech Recognition System–A Literature Review
    M Manjutha, J Gracy, P Subashini, M Krishnaveni
    COMPUTATIONAL METHODS, COMMUNICATION TECHNIQUES AND INFORMATICS, 205- 212 , 2017
    2017.0
    Citations: 17
  • Optimized boundary detection algorithm for postal signs recognition system using variant based Particle Swarm intelligence
    P Subashini, M Krishnaveni, M Manjutha
    2016 International Conference on Computation System and Information … , 2016
    2016.0
    Citations: 3
  • TRACKING VACANT BEDS FOR COVID-19 USING REAL TIME GEOLOCATION
    M MANJUTHA, R PAVIN, N TARUN, P YUVAN SHANKAR
    EXPLORATORY RESEARCH OPPORTUNITIES OF COMPUTING IN LIFE SCIENCES 72, 189 , 0

MOST CITED SCHOLAR PUBLICATIONS

  • Automated Speech Recognition System–A Literature Review
    M Manjutha, J Gracy, P Subashini, M Krishnaveni
    COMPUTATIONAL METHODS, COMMUNICATION TECHNIQUES AND INFORMATICS, 205- 212 , 2017
    2017.0
    Citations: 17
  • An Optimized Cepstral Feature Selection method for Dysfluencies Classification using Tamil Speech Dataset
    M Manjutha, P Subashini, M Krishnaveni, V Narmadha
    2019 IEEE International Smart Cities Conference (ISC2), 671-677 , 2019
    2019.0
    Citations: 10
  • An Optimal Speech Recognition Module for Patient's Voice Monitoring System in Smart Healthcare Applications
    M Krishnaveni, P Subashini, J Gracy, M Manjutha
    2018 Renewable Energies, Power Systems & Green Inclusive Economy (REPS-GIE), 1-6 , 2018
    2018.0
    Citations: 4
  • Survey on nature inspired algorithm for smart city applications
    TT Dhivyaprabha, M Manjutha, P Subashini
    Proceedings of the Mediterranean Symposium on Smart City Application, 1-13 , 2017
    2017.0
    Citations: 4
  • Optimized boundary detection algorithm for postal signs recognition system using variant based Particle Swarm intelligence
    P Subashini, M Krishnaveni, M Manjutha
    2016 International Conference on Computation System and Information … , 2016
    2016.0
    Citations: 3
  • Particle Swarm Optimization based Voice Activity Detection for Stuttered Tamil Speech
    Manjutha, Subashini
    International Journal of Computer Engineering and Applications (IJCEA) 11, 1-14 , 2017
    2017.0
    Citations: 2
  • Survey on optimization algorithms in speech processing
    SP Manjutha, M.
    International Journal of Health Sciences 6 (S5), 2997-3017 , 2022
    2022.0
    Citations: 1
  • Analysis of Tamil Stuttered Speech Using Computational Intelligence
    M Manjutha
    Avinashilingam University , 2022
    2022.0
  • Statistical Model-Based Tamil Stuttered Speech Segmentation Using Voice Activity Detection
    M Manjutha, P Subashini
    Journal of Positive School Psychology 6 (8), 1461-1473 , 2022
    2022.0
  • Soil Nutrient Mining: A Hand-Held Device For On-Farm Soil Analysis And Crop Fertility Prediction
    S Sheela, M Madheslu, M Manjutha
    International Journal of Life Science and Pharma Research 12 (22), 110-115 , 2022
    2022.0
  • Scalable And Secure Sharing of Personal Health Records In Cloud Computing Using Attribute-Based Encryption
    Manjutha M, Arun Kumar K, Subha Sri V, Shree Dharshana D
    International Journal of Life Science and Pharma Research 12 (20), 80-91 , 2022
    2022.0
  • Cauliflower Disease Identification Using Image Segmentation Based on PSO K-Means Clustering
    SS Manjutha M
    International Journal of Life Science and Pharma Research 12 (22), 26-32 , 2022
    2022.0
  • Analysis on Regularity of Speech Energy based on Optimal Thresholding for Tamil Stuttering Dataset
    M Manjutha, P Subashini, M Krishnaveni
    2019 IEEE International Smart Cities Conference (ISC2), 143-149 , 2019
    2019.0
  • Vocal Tone Analysis for Identification of Stuttering Levels based on Tamil Syllable
    MK M. Manjutha, P. Subashini
    International Journal of Recent Technology and Engineering (IJRTE) 8 (2 … , 2019
    2019.0
  • TRACKING VACANT BEDS FOR COVID-19 USING REAL TIME GEOLOCATION
    M MANJUTHA, R PAVIN, N TARUN, P YUVAN SHANKAR
    EXPLORATORY RESEARCH OPPORTUNITIES OF COMPUTING IN LIFE SCIENCES 72, 189 , 0