Academic Journals Database
Disseminating quality controlled scientific knowledge

A Fuzzy Neural Network for Speech Recognition

Author(s): A.Vijay kumar | Aruna | M.Vijayapal Reddy

Journal: ARPN Journal of Systems and Software
ISSN 2222-9833

Volume: 1;
Issue: 9;
Start page: 284;
Date: 2011;
VIEW PDF   PDF DOWNLOAD PDF   Download PDF Original page

Keywords: T-S fuzzy neural network | speech recognition | fuzzy rules

There are two problems when conditional T-S fuzzy Neural network is used directly in speech recognition system. One is the ruledisaster problem, that is, the rule number will increase exponentially with the increase of input dimensions. Another problem is the network reasoning failure resulted from input dimensions too large. The paper presented an improved algorithm of T-S fuzzy neural network. The subtraction clustering algorithm was used to make certain rule number to escape the rule disaster. The network reasoning can correctly work by adding a compensated factor on membership. The improved algorithm was used in speech recognition system. The experimental results showed that the recognition results of improved algorithm are better than the ones of radial basis function (RBF) neural network using Kmeans clustering algorithm to select the centroid. And it has much better robustness.
Why do you need a reservation system?      Affiliate Program