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Proceedings Paper

Phoneme fuzzy characterization in speech recognition systems
Author(s): Francesco Beritelli; Luca Borrometi; Antonino Cuce
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Paper Abstract

The acoustic approach to speech recognition has an important advantage compared with pattern recognition approach: it presents a lower complexity because it doesn't require explicit structures such as the hidden Markov model. In this work, we show how to characterize some phonetic classes of the Italian language in order to obtain a speaker and vocabulary independent speech recognition system. A phonetic data base is carried out with 200 continuous speech sentences of 12 speakers, 6 females and 6 males. The sentences are sampled at 8000 Hz and manual labelled with Asystem Sound Impression Software to obtain about 1600 units. We analyzed several speech parameters such as formants, LPC and reflection coefficients, energy, normal/differential zero crossing rate, cepstral and autocorrelation coefficients. The aim is the achievement of a phonetic recognizer to facilitate the so- called lexical access problem, that is to decode phonetic units into complete sense word strings. The knowledge is supplied to the recognizer in terms of fuzzy systems. The utilized software is called adaptive fuzzy modeler and it belongs to the rule generator family. A procedure has been implemented to integrate in the fuzzy system an 'expert' knowledge in order to obtain significant improvements in the recognition accuracy. Up to this point the tests show a recognition rate of 92% for the vocal class, 89% for the fricatives class and 94% for the nasal class, utilizing 1000 phonemes in phase of learning and 600 phonemes in phase of testing. Our intention is to complete the fuzzy recognizer extending this work to the other phonetic classes.

Paper Details

Date Published: 13 October 1997
PDF: 6 pages
Proc. SPIE 3165, Applications of Soft Computing, (13 October 1997); doi: 10.1117/12.279597
Show Author Affiliations
Francesco Beritelli, Univ. di Catania (Italy)
Luca Borrometi, Univ. di Catania (Italy)
Antonino Cuce, Fuzzy Logic Research Group (Italy)


Published in SPIE Proceedings Vol. 3165:
Applications of Soft Computing
Bruno Bosacchi; James C. Bezdek; David B. Fogel, Editor(s)

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