Robust voiced/unvoiced speech classification using fuzzy rules

Author

Beritelli, Francesco ; Casale, Salvatore

Author_Institution

Ist. di Inf. e Telecommun., Catania Univ., Italy

fYear

1997

fDate

7-10 Sep 1997

Firstpage

5

Lastpage

6

Abstract

The paper presents a robust voiced/unvoiced speech classifier based on fuzzy logic. More specifically, the classification is based on a pattern recognition approach in which the matching phase is performed using a set of 5 fuzzy rules obtained by training. Certain interesting statistical properties of the fuzzy system allow the transition threshold to be adapted to the level of background noise. The results show that the performance of the fuzzy classifier in the presence of various types of background noise is better than that of traditional methods

Keywords

fuzzy logic; pattern classification; speech coding; background noise; fuzzy classifier; fuzzy logic; fuzzy rules; matching phase; pattern recognition approach; performance; robust unvoiced speech classification; robust voiced speech classification; statistical properties; training; transition threshold; Background noise; Databases; Fuzzy systems; Robustness; Signal processing; Signal to noise ratio; Speech coding; Speech processing; Testing; Tongue;

fLanguage

English

Publisher

ieee

Conference_Titel

Speech Coding For Telecommunications Proceeding, 1997, 1997 IEEE Workshop on

Conference_Location

Pocono Manor, PA

Print_ISBN

0-7803-4073-6

Type

conf

DOI

10.1109/SCFT.1997.623868

Filename

623868