Identification and Classification of Fricatives in Speech Using Zero Time Windowing Method

RaviShankar Prasad, Bayya Yegnanarayana


Fricatives are produced by creating a turbulence in the air-flow by passing it through a stricture in the vocal tract cavity. Fricatives are characterized by their noise-like behavior, which makes it difficult to analyze. Difference in the place of articulation leads to different classes of fricatives. Identification of fricative segment boundaries in speech helps in improving the performance of several applications. The present study attempts towards the identification and classification of fricative segments in continuous speech, based on the statistical behavior of instantaneous spectral characteristics. The proposed method uses parameters such as the dominant resonance frequencies, the center of gravity along with the statistical moments of the spectrum obtained using the zero time windowing (ZTW) method. The ZTW spectra exhibits a high temporal resolution and therefore gives accurate segment boundaries in speech. The proposed algorithm is tested on the TIMIT dataset for English language. A high identification rate of 97.5% is achieved for segment boundaries of the sibilant fricative class. Voiced nonsibilants show a lower identification rate than their voiceless counterparts due to their vowel-like spectral characteristics. A high classification rate of 93.2% is achieved between sibilants and nonsibilants.


 DOI: 10.21437/Interspeech.2018-1958

Cite as: Prasad, R., Yegnanarayana, B. (2018) Identification and Classification of Fricatives in Speech Using Zero Time Windowing Method. Proc. Interspeech 2018, 187-191, DOI: 10.21437/Interspeech.2018-1958.


@inproceedings{Prasad2018,
  author={RaviShankar Prasad and Bayya Yegnanarayana},
  title={Identification and Classification of Fricatives in Speech Using Zero Time Windowing Method},
  year=2018,
  booktitle={Proc. Interspeech 2018},
  pages={187--191},
  doi={10.21437/Interspeech.2018-1958},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1958}
}