Now showing items 1-4 of 4

    • 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 ...
    • Classification of speech dysfluencies with MFCC and LPCC features 

      Ooi, Chia Ai; Muthusamy, Hariharan, Dr.; Sazali, Yaacob, Prof. Dr.; Lim, Sin Chee (Elsevier Ltd., 2012-02)
      The goal of this paper is to discuss comparison of speech parameterization methods: Mel-Frequency Cepstrum Coefficients (MFCC) and Linear Prediction Cepstrum Coefficients (LPCC) for recognizing the stuttered events. Speech ...
    • Comparison of speech parameterization techniques for the classification of speech disfluencies 

      Chong, Yen Fook; Hariharan, Muthusamy, Dr.; Lim, Sin Chee; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Prof. Dr. (Scientific and Technical Research Council of Turkey, 2013-12)
      Stuttering assessment through the manual classification of speech disfluencies is subjective, inconsistent, time-consuming, and prone to error. The aim of this paper is to compare the effectiveness of the 3 speech feature ...