Title :
Classification of speech accents with neural networks
Author :
Chan, Mike V. ; Feng, Xin ; Heinen, James A. ; Niederjohn, Russell J.
Author_Institution :
Dept. of Electr. & Comput. Eng., Marquette Univ., Milwaukee, WI, USA
fDate :
27 Jun-2 Jul 1994
Abstract :
Several neural network models including competitive learning and counter propagation are developed to identify individuals as either native or non-native speakers based on their accents. Some important speech features, such as pitch period and the first three formant frequencies, are used as inputs to the neural networks. Comparison results based on experiments are also presented. The primary contribution is that it provides a feasible approach for an assisting automatic speech recognition system in an environment in which different English accents may be used
Keywords :
neural nets; pattern classification; speech recognition; unsupervised learning; English accents; automatic speech recognition system; competitive learning; counter propagation; formant frequencies; native speakers; neural networks; nonnative speakers; pitch period; speech accents classification; Artificial neural networks; Automatic speech recognition; Computer architecture; Counting circuits; Frequency; Neural networks; Pattern recognition; Speech processing; Speech recognition; Supervised learning;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374994