TITLE:
Enhancing the Efficiency of Voice Controlled Wheelchairs Using NAM for Recognizing Partial Speech in Tamil
AUTHORS:
Angappan Kumaresan, Nagarajan Mohankumar, Mathavan Sureshanand, Jothi Suganya
KEYWORDS:
NAM, Speech Recognition, TSRE, Wheelchair Guidance, HCI
JOURNAL NAME:
Circuits and Systems,
Vol.7 No.10,
August
5,
2016
ABSTRACT: In this paper, we have
presented an effective method for recognizing partial speech with the help of
Non Audible Murmur (NAM) microphone which is robust against noise. NAM is a
kind of soft murmur that is so weak that even people nearby the speaker cannot
hear it. We can recognize this NAM from the mastoid of humans. It can be
detected only with the help of a special type of microphone termed as NAMmicrophone. We can use this approach
for impaired people who can hear sound but can speak only partial words
(semi-mute) or incomplete words. We can record and recognize partial speech
using NAM microphone. This approach can be used to solve problems for paralysed
people who use voice controlled wheelchair which helps them to move around
without the help of others. The present voice controlled wheelchair systems can
recognize only fully spoken words and can’t recognise words spoken by semi-mute
or partially speech impaired people. Further it uses normal microphone which hassevere
degradation and external noise influence when used for recognizing partial
speech inputs from impaired people. To overcome this problem, we can use NAM
microphone along with Tamil Speech Recognition Engine (TSRE) to improve the
accuracy of the results. The proposed method was designed and implemented in a
wheelchair like model using Arduino microcontroller kit. Experimental results
have shown that 80% accuracy can be obtained in this method and also proved
that recognizing partially spoken words using NAM microphone was much efficient
compared to the normal microphone.