Title :
Speaker Accent Classification System using Fuzzy Canonical Correlation-Based Gaussian Classifier
Author :
Ullah, Sameeh ; Karray, Fakhri
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON, Canada
Abstract :
A speaker´s accent is the most important factor affecting the performance of automatic speech recognition (ASR) systems because accents vary widely, even within the same country or community. The reason may be attributed to the fuzziness between the boundaries of phoneme classes, a result of differences in a speaker´s vocal tract and accent. In this paper, a new method is proposed that is based on the fuzzy canonical correlation-based Gaussian classifier. In the proposed method the membership values of the clusters are based not only on minimizing the distance between the cluster centroids, but also maximizing the out-of-class variations.
Keywords :
Gaussian processes; fuzzy set theory; speaker recognition; Gaussian classifier; automatic speech recognition systems; cluster centroids; fuzzy canonical correlation; out-of-class variations; speaker accent classification system; Anatomy; Automatic speech recognition; Clustering algorithms; Degradation; Fuzzy systems; Hidden Markov models; Neural networks; Signal processing; Support vector machine classification; Support vector machines; Fuzzy canonical correlation; Gaussian classifier; speaker´s accent; vocal tract;
Conference_Titel :
Signal Processing and Communications, 2007. ICSPC 2007. IEEE International Conference on
Conference_Location :
Dubai
Print_ISBN :
978-1-4244-1235-8
Electronic_ISBN :
978-1-4244-1236-5
DOI :
10.1109/ICSPC.2007.4728438
