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Spectral and textural feature-based system for automatic detection of fricatives and affricates

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3 Author(s)
Ruinskiy, D. ; Dept. of Comput. Sci., Tel-Hai Coll., Tel-Hai, Israel ; Dadush, N. ; Lavner, Y.

Phoneme spotting in continuous speech has various applications - in speech recognition, smart audio filtering, multimedia synchronization and other fields. Many studies on phoneme spotting have been conducted, using different approaches. We present two algorithms for spotting fricatives (such as /s/, /sh/, /f/) and affricates (/ts/, /ch/) - one based on a cepstrogram-matching approach, and the other on an LDA classifier with a feature vector constructed from temporal, spectral and textural features of the audio signal. Tested on a selection of speech and song recordings, the algorithms demonstrate correct identification rate of over 90% and specificity of over 85%.

Published in:

Electrical and Electronics Engineers in Israel (IEEEI), 2010 IEEE 26th Convention of

Date of Conference:

17-20 Nov. 2010