Title
Malay Isolated Speech Recognition Using Neural Network: A Work In Finding Number Of Hidden Nodes And Learning Parameters
Abstract
This paper explains works in speech recognition using neural network. The main objective of the experiment is to choose suitable number of nodes in hidden layer and learning parameters for malay ilsolated digit speech problem through trial and error method. The network used in the experiment is feed forward multilayer perception trained with back propagation scheme. Speech data for the study are analyzed using linear predictive coding and log area ratio to represent speech signal for every 20ms through a fixed overlapped windows. The neural network learning operation is greatly influenced by the parameters i.e., momentum, learning rate and number of hidden nodes chosen. The result shows that choosing unsuitable parameters lead to unlearned network while some good parameters set from previous work perform badly in this application. Best recognition rate achieved was 95% using network topology of input nodes, hidden nodes and output nodes of size 320:45:4 respectively while the best momentum rate and learning rate in the experiment were 0.5 and 0.75.
Year
Venue
Keywords
2011
INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY
Speech recognition, neural network, learning parameters, trial and error method
Field
DocType
Volume
Computer science,Time delay neural network,Multilayer perceptron,Artificial intelligence,Artificial neural network,Linear predictive coding,Trial and error,Pattern recognition,Speech recognition,Network topology,Backpropagation,Machine learning,Feed forward
Journal
8
Issue
ISSN
Citations 
4
1683-3198
2
PageRank 
References 
Authors
0.48
3
3
Name
Order
Citations
PageRank
Md Sah Bin Hj Salam171.36
Dzulkifli Mohamad29613.41
Sheikh Hussain Salleh3375.62