Abstract
People who are paralyzed, confront numerous challenges in meeting their basic necessities on a daily basis. It is very difficult to understand the speech of people with dysarthria, amyotrophic lateral sclerosis (ALS) and similar conditions. Automatic speech command recognition system will enhance the lifestyle of people with voice disorder like dysarthria and paraplegics. The proposed work will convert the speech command of paralyzed people into text and send it to the care taker's mobile with the help of Twilio message services. Algorithms like Support Vector Machine (SVM) and Convolutional Neural network (CNN) model is used for speech command identification and speech to text conversion. CNN model yields an accuracy of 90.62%, whereas the SVM algorithm gives a very low accuracy. The developed TensorFlow model is deployed in the flask server.
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