IoT Based Sign Language Recognition System

Sign language is the key communication medium which deaf and mute people use in their day-to-day life Talking to disabled people will cause a difficult situation since a non- mute person cannot understand their hand gestures and in many instances mute people are hearing impaired Same as Sinhala Tamil English or any other language sign language also tend to have differences according to the region This paper is an attempt to assist deaf and mute people to develop an effective communication mechanism with non-mute people The end product of this project is a combination of a mobile application that can translate the sign language into digital voice and IoT enabled light-weighted wearable glove which capable of recognizing twenty-six English alphabet 0-9 numbers and words Better user experience provide with voice-to-text feature in mobile application to reduce the communication gap within mute and non-mute communities Research findings and results from current system visualize the output of the product can be optimized up to 25 -35 with enhanced pattern recognition mechanis

Mapping the evolving landscape of child-computer interaction research: structures and processes of knowledge (re)production

Implementing an iterative sequential mixed methods design (Quantitative → Qualitative → Quantitative) framed within a sociology of knowledge approach to discourse, this study offers an account of the structure of the field of Child-Computer Interaction (CCI), its development over time, and the practices through which researchers have (re)structured knowledge comprising the field. Thematic structure of knowledge within the field, and its evolution over time, is quantified through implementation of a Correlated Topic Model (CTM), an automated inductive content analysis method, in analysing 4,771 CCI research papers published between 2003 and 2021. Detailed understanding of practices through which researchers (re)structure knowledge within the field, including factors influencing these practices, is obtained through thematic analysis of online workshops involving prominent contributors to the field (n=7). Strategic practices utilised by researchers in negotiating tensions impeding integration of novel concepts in the field are investigated through analysis of semantic features of retrieved papers using linear and negative binomial regression models. Contributing an extensive mapping, results portray the field of CCI as a varied research landscape, comprising 48 major themes of study, which has evolved dynamically over time. Research priorities throughout the field have been subject to influence from a range of endogenous and exogenous factors which researchers actively negotiate through research and publication practices. Tacitly structuring research practices, these factors have broadly sustained a technology-driven, novelty-dominated paradigm throughout the field which has failed to substantively progress cumulative knowledge. Through strategic negotiation of persistent tensions arising as consequence of these factors, researchers have nonetheless affected structural change within the field, contributing to a shift towards a user needs-driven agenda and progression of knowledge therein. Findings demonstrate that the field of CCI is proceeding through an intermediary phase in maturation, forming an increasingly distinct disciplinary shape and identity through the cumulative structuring effect of community members’ continued negotiation of tensions

Exploring sensor gloves for teaching children sign language

This research investigates if a computer and an alternative input device in the form of sensor gloves can be used in the process of teaching children sign language. The presented work is important, because no current literature investigates how sensor gloves can be used to assist children in the process of learning sign language. The research presented in this paper has been conducted by assembling hardware into sensor gloves, and by designing software capable of (i) filtering out sensor noise, (ii) detecting intentionally posed signs, and (iii) correctly evaluating signals in signs posed by different children. Findings show that the devised technology can form the basis of a tool that teaches children sign language, and that there is a potential for further research in this area

Exploring sensor gloves for teaching children sign language

This research investigates if a computer and an alternative input device in the form of sensor gloves can be used in the process of teaching children sign language. The presented work is important, because no current literature investigates how sensor gloves can be used to assist children in the process of learning sign language. The research presented in this paper has been conducted by assembling hardware into sensor gloves, and by designing software capable of (i) filtering out sensor noise, (ii) detecting intentionally posed signs, and (iii) correctly evaluating signals in signs posed by different children. Findings show that the devised technology can form the basis of a tool that teaches children sign language, and that there is a potential for further research in this area. © 2012 Kirsten Ellis and Jan Carlo Barca