SignsWorld: Deeping into the Silence World and Hearing Its Signs (State of the Art)

Abstract

Automatic speech processing systems are employed more and more often in real environments. Although the underlying speech technology is mostly language independent, differences between languages with respect to their structure and grammar have substantial effect on the recognition systems performance. In this paper, we present a review of the latest developments in the sign language recognition research in general and in the Arabic sign language (ArSL) in specific. This paper also presents a general framework for improving the deaf community communication with the hearing people that is called SignsWorld. The overall goal of the SignsWorld project is to develop a vision-based technology for recognizing and translating continuous Arabic sign language ArSL.

Indian sign language recognition: An approach based on fuzzy-symbolic data

“…The sign language recognition research works have been addressed at finger spelling level in [2,13,14,23,26,27], at word level [12,17,26] and at sentence level [4,16,17]. The techniques which gained importance due to their performance by research community are Ichetrichef moments [7], Gray level histogram [31], Sensor based glove technique [7,8,11,21], Hidden Morkov Models (HMM) [1], Hu moments and Electromyography (EMG) segmentation [1], Localized contour sequence [11], Size function [19], Transitionmovement [6], Moment based size function [9], Convex chain coding and Basic chain code [21], Fourier descriptors [23], Grassman Covariance Matrix (GCM) [33], Fusion of appearance based and 5DT glove based features [21], Sparse Observation (SO) description [29].…”

Hand Gesture Recognition System Based on a Geometric Model and Rule Based Classifier

“…A three-dimensional discrete histogram h object (r, g, b) can be used to represent the dimensions corresponding to the red, green, and blue components. The total sum of h object over all colors is therefore equal to the number of considered object pixels n object , ∑ r ∑ g ∑ b h object (r,g,b)=n object (1) Given a pixel from the object, the probability of it having a certain color (r, g, b) can be computed from h object as P(r,g,b|object)=h object (r,g,b)/n object (2) By creating a complementary histogram h bg of the background colors we will have the probability for the background in the same way:…”

“…Gestures are a powerful means of communication among humans. However, gesturing is deeply steadfast in human communication that people often continue gesturing when speaking together in daily life [1,2].…”

SignsWorld Atlas; a benchmark Arabic Sign Language database

“…In addition, SL became powerful enough to fulfill the needs of the deaf people in their day to day life. SL is also a subset of the gestured communication used in deaf-mute society (Khan et al, 2009 andRiad et al, 2012). ASLR systems are being developed for daily communication between the deaf and the hearing persons (Wang andWang, 2006 andMalima et al, 2006).…”