Integrated Speaker and Speech Recognition for Wheel Chair Movement Using Artificial Intelligence

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Abstract

A speech signal is a result of the constrictions of vocal tract and different sounds can be generated by different vocal tract constrictions. A speech signal carries two things i.e. speaker's identity and meaning. For a specific applications of speaker and speech recognition like voice operated wheel chair, both the speaker and speech is to be recognized for movement of wheel chair. Automation in wheelchair is, today's requirement as the numbers of people are increasing with disabilities like injuries in spine, amputation, impairments in hands etc. They need assistance for moving their wheel chair. Voice operated wheel chair is one of the solution. The intention of this study is to use a speaker and speech dependent system to control the wheelchair and minimize the risk of unwanted accident. We have proposed a system in which speaker (patient) as well as speech (commands) is recognized based upon the acoustic features like Mel Frequency Cepstral Coefficients (MFCC). Optimization of the features using Artificial Bee Algorithm (ABC) is done to gain good accuracy with artificial intelligence technique as a classifier. We have tested our system on standard dataset (TIDIGITS) and our own prepared dataset. Also, validation of proposed work is done by generating control signal to actuate the wheel chair in real time scenario.

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