Conversion of Sign Language to Spoken Sentences by Means of a Sensory Glove

Abstract

Normal communication of deaf people in ordinary life still remains an unrealized task, despite the fact that Sign Language Recognition (SLR) made a big improvement in recent years. We want here to address this problem proposing a portable and low cost system, which demonstrated to be effective for translating gestures into written or spoken sentences. This system relies on a home-made sensory glove, used to measure the hand gestures, and on Wavelet Analysis (WA) and a Support Vector Machine (SVM) to classify the hand's movements. In particular we devoted our efforts to translating the Italian Sign Language (LIS, Linguaggio Italiano dei Segni), applying WA for feature extractions and SVM for the classification of one hundred different dynamic gestures. The proposed system is light, not intrusive or obtrusive, to be easily utilized by deaf people in everyday life, and it has demonstrated valid results in terms of signs/words conversion.