Self-similarity Matrix Based Intelligibility Assessment of Cleft Lip and Palate Speech

Sishir Kalita, S R Mahadeva Prasanna, Samarendra Dandapat


This work presents a comparison based framework by exploiting the self-similarity matrices matching technique to estimate the speech intelligibility of cleft lip and palate (CLP) children. Self-similarity matrix (SSM) of a feature sequence is a square matrix, which encodes the acoustic-phonetic composition of the underlying speech signal. Deviations in the acoustic characteristics of underlying sound units due to the degradation of intelligibility will deviate the CLP speech’s SSM structure from that of normal. This degree of deviations in CLP speech’s SSM from the corresponding normal speech’s SSM may provide information about the severity profile of speech intelligibility. The degree of deviations is quantified using the structural similarity (SSIM) index, which is considered as the representative of objective intelligibility score. The proposed method is evaluated using two parameterizations of speech signals: Mel-frequency cepstral coefficients and Gaussian posteriorgrams and compared with dynamic time warping (DTW) based intelligibility assessment method. The proposed SSM based method shows the better correlation with the perceptual ratings of intelligibility when compared to the DTW based method.


 DOI: 10.21437/Interspeech.2018-1125

Cite as: Kalita, S., Prasanna, S.R.M., Dandapat, S. (2018) Self-similarity Matrix Based Intelligibility Assessment of Cleft Lip and Palate Speech. Proc. Interspeech 2018, 367-371, DOI: 10.21437/Interspeech.2018-1125.


@inproceedings{Kalita2018,
  author={Sishir Kalita and S R Mahadeva Prasanna and Samarendra Dandapat},
  title={Self-similarity Matrix Based Intelligibility Assessment of Cleft Lip and Palate Speech},
  year=2018,
  booktitle={Proc. Interspeech 2018},
  pages={367--371},
  doi={10.21437/Interspeech.2018-1125},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1125}
}