Browsing Hariharan Muthusamy, Dr. by Subject "Acoustic analysis"

Now showing items 1-12 of 12

    • 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 ...

    • Automatic classification of infant cry: A review 

      Saraswathy, J.; Muthusamy, Hariharan, Dr.; Sazali, Yaacob, Prof. Dr.; Wan Khairunizam, Wan Ahmad, Dr, (Institute of Electrical and Electronics Engineers (IEEE), 2012-02-27)
      This paper reviews the some of significant works on infant cry signal analysis proposed in the past two decades and reviews the recent progress in this field. The cry of baby cannot be predicted accurately where it is very ...

    • 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- ...

    • 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 ...

    • Infant cry classification: time frequency analysis 

      Saraswathy, Jeyaraman; Hariharan, Muthusamy, Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr.; Thiyagar., N (IEEE Conference Publications, 2013-11)
      Acoustic analysis of infant cry has been the subject of a number of researchers since half decades ago. This paper addresses a simple time-frequency analysis based signal processing technique using short-time Fourier ...

    • Normal and hypoacoustic infant cry signal classification using time-frequency analysis and general regression neural network 

      Hariharan, Muthusamy, Dr.; Sindhu, R; Sazali, Yaacob, Prof. Dr. (Elsevier Ireland Ltd., 2012-11)
      Crying is the most noticeable behavior of infancy. Infant cry signals can be used to identify physical or psychological status of an infant. Recently, acoustic analysis of infant cry signal has shown promising results and ...

    • Pathological infant cry analysis using wavelet packet transform and probabilistic neural network 

      Muthusamy, Hariharan; Sazali, Yaacob, Prof. Dr.; Saidatul Ardeenaawatie, Awang (Elsevier Ltd., 2011-11)
      A new approach has been presented based on the wavelet packet transform and probabilistic neural network (PNN) for the analysis of infant cry signals. Feature extraction and development of classification algorithms play ...

    • 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. ...