Abstract
This paper presents the fusion of artificial intelligence (AI) learning algorithms that combined genetic algorithms (GA) and neural network (NN) methods. These both methods were used to find the optimum weights for the hidden and output layers of feed-forward artificial neural network (ANN) model. Both algorithms are the separate modules and we proposed dynamic connection strategy for combining both algorithms to improve the recognition performance for isolated spoken Malay speech recognition. There are two different GA techniques used in this research, one is standard GA and slightly different technique from standard GA also has been proposed. Thus, from the results, it was observed that the performance of proposed GA algorithm while combined with NN shows better than standard GA and NN models alone. Integrating the GA with feed-forward network can improve mean square error (MSE) performance and with good connection strategy by this two stage training scheme, the recognition rate can be increased up to 99%.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
