ISCA Archive SpeechProsody 2010
ISCA Archive SpeechProsody 2010

Syllable classification using static matrices and prosodic features

Bogdan Ludusan, Antonio Origlia, Francesco Cutugno

In this paper we explore the usefulness of prosodic features for syllable classification. In order to do this, we represent the syllable as a static analysis unit such that its acoustic-temporal dynamics could be merged into a set of features that the SVM classifier will consider as a whole. In the first part of our experiment we used MFCC as features for classification, obtaining a maximum accuracy of 86.66%. The second part of our study tests whether the prosodic information is complementary to the cepstral information for syllable classification. The results obtained show that combining the two types of information does improve the classification, but further analysis is necessary for a more successful combination of the two types of features.

Index Terms: syllable, SVM, prosodic features

Cite as: Ludusan, B., Origlia, A., Cutugno, F. (2010) Syllable classification using static matrices and prosodic features. Proc. Speech Prosody 2010, paper 830

  author={Bogdan Ludusan and Antonio Origlia and Francesco Cutugno},
  title={{Syllable classification using static matrices and prosodic features}},
  booktitle={Proc. Speech Prosody 2010},
  pages={paper 830}