Voice Controlled Wheelchair - V, Shwetha; Mani, Vaibhav; Kumaran, Aditya (International Journal of Engineering and Technology, 2018)
The objective of this work is to facilitate the movement of people with physical disabilities rendering them incapable of independent movement and grants a degree of simplicity to those who lack the dexterity to control a joystick and had been achieved with the help of voice recognition model for the maneuvering of the wheelchair hence making it hands free and simplistic and can be added to existing wheel chair .The hardware is comprised of a wooden box designed in house open at one end, the wood used is plywood and the frame has a load withstanding capacity of 50 kg. The software implementation is the implementation of voice recognition on a Ubuntu distribution with the help of the CMU Sphinx Toolkit and the Pocket sphinx library. The coding for the voice recognition is done on a python platform using both Python 2.7 and 3.5 IDE as it is open source. The Arduino coding has been done in Ubuntu using the Arduino Software. In this work, two methods are used for voice recognition namely Key phrase Spotting and Sliding Match Filter and tested in different test environment. Using  Keyphrase method  gives a mean accuracy of up to 75%  and maximum of 90% in noisy environment and tested in different environment along with fine tuning ,Successfully designed a voice controlled wheelchair with very quick response time along with voice recognition. Keyphrase spotting algorithm it is by far the more efficient system as compared to more robust Sliding match algorithm.
Keywords: Voice Recognition; API; Speech Recognition; CMU Sphinix; Audio length Keyphrase Spotting; Sliding Match ï¬lter; Unidirectional microphone.