Title :
Synthesis and performance analysis of a Recurrent Fuzzy Multilayer Perceptron for speech recognition
Author_Institution :
Dept. of IT, Bharati Vidyapeeth´´s Coll. of Eng., New Delhi, India
Abstract :
A novel speech recognition method has been proposed which combines the capabilities of a Recurrent Fuzzy Multilayer Perceptron (MLP) to the existing Mel Frequency Cepstral Coefficients (MFCC) model, synthesized using JAVA. Performance analysis of the proposed recurrent fuzzy MLP relative to a speech recognition system has been shown using MATLAB. Owing to its short-term memory effect in addition to inherent neuro-fuzzy model advantages, the simulation results obtained were significantly better than offered by a crisp neural network.
Keywords :
Java; cepstral analysis; multilayer perceptrons; recurrent neural nets; speech recognition; JAVA; MATLAB; Mel frequency cepstral coefficients model; recurrent fuzzy multilayer perceptron; speech recognition method; Analytical models; Artificial neural networks; Frequency synthesizers; Hidden Markov models; Mel frequency cepstral coefficient; Nerve fibers; Speech recognition; artificial neural networks; fuzzy logic; multilayer perceptron; recurrent neural networks; speech recognition;
Conference_Titel :
Methods and Models in Computer Science (ICM2CS), 2010 International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-1-4244-9701-0
DOI :
10.1109/ICM2CS.2010.5706713
