Browsing Hariharan Muthusamy, Dr. by Author "paul@unimap.edu.my"

Now showing items 1-8 of 8

    • Automatic detection of voice disorders using self loop architecture in back propagation network 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Anna University, 2008-01-04)
      Acoustic analysis is a non-invasive technique to detect the voice disorders and diagnose the vocal and voice disease. In the recent years, voice disease are increasing dramatically due to unhealthy social habits and voice ...

    • 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 voice disorders using band energy spectrum in wavelet domain 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr. (Universiti Malaysia Perlis (UniMAP), 2008-03-08)
      In the evolution of quality of speech, acoustic analyses of normal and pathological voices have become increasingly interesting to researchers in laryngology and speech pathologies. Vocal signal information plays an important ...

    • 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 ...

    • Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders 

      Murugesa Pandian, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr. (SpringerLink, 2008-06-25)
      Feature extraction from the vocal signal plays very important role in the area of automatic detection of voice disorders. Many feature extraction algorithms have been developed in the last three decades based on acoustic ...

    • Identification of vocal and voice disorders 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Rizon, Mohammed Juhari, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Universiti Malaysia Perlis (UniMAP), 2007-10-25)
      The discrimination of normal and pathological voices using noninvasive acoustic analysis helps to perform accurate identification of voice disorders and diagnoses of vocal and voice disease. Acoustic analysis is a non- ...

    • Neural network based detection of voice disorders using energy spectrum and equal-loudness contours 

      Murugesa Pandian, Paulraj, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Universiti Teknologi MARA (UiTM)Faculti of Electrical Engineering, 2008-03-07)
      Impairment of vocal function can have a major impact on the quality of life, severely limiting communication at work and affecting all social aspect of daily life. In the recent years, voice disease are increasing dramatically ...

    • 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. ...