Real time wearable speech recognition system for deaf persons

Abstract

Abstract Numerous people around the world experience varying degrees of hearing difficulties. A sense of sound is critical for quality of life for people with hearing difficulties, including deaf people. Wearable devices have substantial potential for voice recognition applications owing to their low cost and light weight. They can assist deaf people perform their daily activities more easily without requiring assistance from others. I have designed and developed a wearable, vibration-based system that will enable deaf people to distinguish important sentences, thereby improving their quality of life. The device consists of a microphone and vibration motor and is mounted on the user’s back. A study was conducted with the device in which speech was detected using Mel Frequency Cepstral Coefficients (MFCC), pre-processing, and Dynamic Time Warping (DTW). Tests were conducted in three different signal-to-noise ratio environments in real time with a typical computer setup. The results had 95% accuracy, 97% specificity and 76% sensitivity.