Browsing Sazali Yaacob, Prof. Dr. by Author "Hariharan, Muthusamy"

Now showing items 1-13 of 13

    • Analysis of infant cry through weighted linear prediction cepstral coefficients and probabilistic neural network 

      Hariharan, Muthusamy; Lim, Sin Chee; Sazali, Yaacob, Prof. Dr. (Springer Science+Business Media, LLC., 2012)
      Acoustic analysis of infant cry signals has been proven to be an excellent tool in the area of automatic detection of pathological status of an infant. This paper investigates the application of parameter weighting for ...

    • Classification of speech dysfluencies using LPC based parameterization techniques 

      Hariharan, Muthusamy; Lim, Sin Chee; Ooi, Chia Ai; Sazali, Yaacob, Prof. Dr. (Springer Science+Business Media, LLC., 2011-01-20)
      The goal of this paper is to discuss and compare three feature extraction methods: Linear Predictive Coefficients (LPC), Linear Prediction Cepstral Coefficients (LPCC) and Weighted Linear Prediction Cepstral Coefficients ...

    • Detection of vocal fold paralysis and edema using time-domain features and probabilistic neural network 

      Hariharan, Muthusamy; Paulraj, Murugesa Pandiyan, Assoc. Prof.; Sazali, Yaacob, Prof. Dr. (Inderscience Publisher, 2011)
      This paper proposes a feature extraction method based on time-domain energy variation for the detection of vocal fold pathology. In this work, two different vocal fold problems (vocal fold paralysis and edema) are taken ...

    • Diagnosis of voices disorders using MEL scaled WPT and functional link neural network 

      Paulraj, Muregesa Pandiyan, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Hariharan, Muthusamy (Biomedical Fuzzy Systems Association (BMFSA), 2008-03-31)
      Nowadays voice disorders are increasing dramatically due to the modern way of life. Most of the voice disorders cause changes in the voice signal. Acoustic analysis on the speech signal could be a useful tool for ...

    • Identification of vocal fold pathology based on Mel Frequency Band Energy Coefficients and singular value decomposition 

      Hariharan, Muthusamy; Paulraj, Murugesa Pandiyan, Assoc. Prof.; Sazali, Yaacob, Prof. Dr. (Institute of Electrical and Elctronics Engineering (IEEE), 2009-11-18)
      Many approaches have been developed to detect the vocal fold pathology. Among the approaches, analysis of speech has proved to be an excellent tool for vocal fold pathology detection. This paper presents the Mel Frequency ...

    • Improved back propagation neural network for the diagnosis of pathological voices 

      Paulraj, M.P.; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Hariharan, Muthusamy (Association for Advancedment of Modelling and Simulation Techniques in Entreprises (A.M.S.E), 2008)
      Most of vocal and voice diseases cause changes in the voice. ENT clinicians use acoustic voice analysis to characterize the pathological voices. Nowadays, voice diseases are increasing dramatically due to unhealthy social ...

    • Investigation of vision impairments using pattern reversal VEPs and extreme learning machine 

      Vijean, Vikneswaran; Hariharan, Muthusamy; Sazali, Yaacob, Prof. Dr. (Universiti Malaysia Perlis (UniMAP), 2012-06-18)
      Analysis of vision impairment using pattern reversal visually evoked potentials (VEP) is gaining interest from researchers. The VEPs are collected using non-invasive EEG electrodes from the scalp overlaying the occipital ...

    • Mathematical model attitude estimation using Kalman filter technique for low earth orbit satellite 

      Nor Hazadura, Hamzah; Sazali, Yaacob, Prof. Dr.; Teoh, Vil Cherd; Siti Maryam, Harun; Hariharan, Muthusamy; Mohamad Nazri, Dol Bahar; Norhizam, Hamzah (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      In space, the attitude analysis of a satellite is constantly being computed within the system of the satellite. In this paper, the linear mathematical model of the satellite attitude control with gravity gradient moment, ...

    • MFCC based recognition of repetitions and prolongations in stuttered speech using k-NN and LDA 

      Lim, Sin Chee; Ooi, Chia Ai; Hariharan, Muthusamy; Sazali, Yaacob, Prof. (Institute of Electrical and Elctronics Engineering (IEEE), 2009-11-16)
      Stuttering is a speech disorder in which the normal flow of speech is disrupted by occurrences of dysfluencies, such as repetitions, interjection and so on. There are a high proportion of repetitions and prolongations in ...

    • Performance comparison of daubechies wavelet family in Infant cry classification 

      Saraswathy, J; Hariharan, Muthusamy; Vijean, Vikneswaran; Sazali, Yaacob, Prof. Dr.; Wan Khairunizam, Wan Ahmad, Dr. (IEEE Conference Publications, 2012)
      Infant cry is a non-stationary, loud, high-pitched signal made by infants in response to certain situations. This acoustic signal can be used to identify physical or psychology status of infant. The aim of this work is to ...

    • Speech emotion recognition using kNN classifier 

      M. N., Hasrul; Hariharan, Muthusamy; Sazali, Yaacob, Prof. Dr. (Universiti Malaysia Perlis (UniMAP), 2012-06-18)
      There are many methods that are commonly used by researches in order to recognize speech of human emotion. In this paper, Surrey audio-visual expressed emotion (SAVEE) database are used for the analysis. The Mel-Frequency ...

    • Supervised neural network classifier for voice pathology 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Hariharan, Muthusamy (Kongu Engineering College, 2008-01-03)
      The classification of normal and pathological voices using noninvasive acoustical analysis features helps speech specialist to perform accurate diagnoses of vocal and voice disease. Acoustic analysis is a non-invasive ...

    • Time-domain features and probabilistic neural network for the detection of vocal fold pathology 

      Hariharan, Muthusamy; Paulraj, Murugesa Pandiyan, Prof. Madya; Sazali, Yaacob, Prof. Dr. (Universiti Malaya, 2010)
      Due to the nature of job, unhealthy social habits and voice abuse, people are subjected to the risk of voice problems. It is well known that most of vocal fold pathologies cause changes in the acoustic voice signal. ...