Browsing Hariharan Muthusamy, Dr. by Subject "Infant cry"

Now showing items 1-7 of 7

    • 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 ...

    • Infant cry classification to identify asphyxia using time-frequency analysis and radial basis neural networks 

      Muthusamy, Hariharan; Jeyaraman, Saraswathy; Sindhu, Ravindran; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (Elsevier Ltd, 2012-08)
      A cry is the first verbal communication of infants and it is described as a loud, high-pitched sound made by infants in response to certain situations. Infant cry signals can be used to identify physical or psychological ...

    • 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 ...

    • 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 ...