When do people start to recognize signs?

Gesture ◽  
2009 ◽  
Vol 9 (2) ◽  
pp. 207-236 ◽  
Author(s):  
Jeroen Arendsen ◽  
Andrea J. van Doorn ◽  
Huib de Ridder
Keyword(s):  
The Netherlands ◽  
Sign Language ◽  
Motor Response ◽  
Time Course ◽  
Lexical Meaning ◽  
Sign Recognition ◽  
Sign Detection ◽  
Participant Characteristics

The aim of this paper is to examine when signers start to recognize the lexical meaning of a sign. This is studied with movies of 32 mono-morphemic signs of Sign Language of the Netherlands (SLN). Signs were presented in isolation or with preceding fidgets (e.g., rubbing your nose). Signers watched these movies at normal playing speed and had to respond as soon as they recognized a sign, which they were able to do, on average, about 850 ms after the coded beginning of the sign. By subtracting the time participants need to generate a motor response to a visible event, which was 310 ms on average, sign recognition was estimated to occur after around 540 ms. The results were further analyzed in relation to the sign’s movement phases (preparation, nucleus, and recovery) and for effects of participant characteristics, sign characteristics, and embedding conditions. The current findings are compared with earlier work on the time course of lexical sign recognition. Moreover, they are compared with findings from an earlier experiment on detecting the beginning of a sign (Arendsen et al., 2007) to study possible interference of lexical recognition with sign detection by signers.

Technological Aids for Deaf and Mute in Modern World

2020 ◽  
Vol 14 ◽  
Author(s):  
Vasu Mehra ◽  
Dhiraj Pandey ◽  
Aayush Rastogi ◽  
Aditya Singh ◽  
Harsh Preet Singh
Keyword(s):  
Sign Language ◽  
Gesture Recognition ◽  
Recognition System ◽  
Modern World ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Background Elimination ◽  
Sign Recognition ◽  
Technological Advances ◽  
Better Than

Background:: People suffering from hearing and speaking disabilities have a few ways of communicating with other people. One of these is to communicate through the use of sign language. Objective:: Developing a system for sign language recognition becomes essential for deaf as well as a mute person. The recognition system acts as a translator between a disabled and an able person. This eliminates the hindrances in exchange of ideas. Most of the existing systems are very poorly designed with limited support for the needs of their day to day facilities. Methods:: The proposed system embedded with gesture recognition capability has been introduced here which extracts signs from a video sequence and displays them on screen. On the other hand, a speech to text as well as text to speech system is also introduced to further facilitate the grieved people. To get the best out of human computer relationship, the proposed solution consists of various cutting-edge technologies and Machine Learning based sign recognition models which have been trained by using Tensor Flow and Keras library. Result:: The proposed architecture works better than several gesture recognition techniques like background elimination and conversion to HSV because of sharply defined image provided to the model for classification. The results of testing indicate reliable recognition systems with high accuracy that includes most of the essential and necessary features for any deaf and dumb person in his/her day to day tasks. Conclusion:: It’s the need of current technological advances to develop reliable solutions which can be deployed to assist deaf and dumb people to adjust to normal life. Instead of focusing on a standalone technology, a plethora of them have been introduced in this proposed work. Proposed Sign Recognition System is based on feature extraction and classification. The trained model helps in identification of different gestures.

10. In Pursuit of Legal Recognition of the Sign Language of the Netherlands

2019 ◽  
pp. 161-175
Author(s):  
Richard Cokart ◽  
Trude Schermer ◽  
Corrie Tijsseling ◽  
Eva Westerhoff
Keyword(s):  
The Netherlands ◽  
Sign Language ◽  
Legal Recognition

Frequency distribution and spreading behavior of different types of mouth actions in three sign languages

2008 ◽  
Vol 11 (1) ◽  
pp. 45-67 ◽  
Author(s):  
Onno A. Crasborn ◽  
Els van der Kooij ◽  
Dafydd Waters ◽  
Bencie Woll ◽  
Johanna Mesch
Keyword(s):  
The Netherlands ◽  
Comparative Study ◽  
Sign Language ◽  
Frequency Distribution ◽  
Sign Languages ◽  
Spreading Behavior ◽  
British Sign Language ◽  
Different Types ◽  
Primary Focus ◽  
British Sign

In this paper, we present a comparative study of mouth actions in three European sign languages: British Sign Language (BSL), Nederlandse Gebarentaal (Sign Language of the Netherlands, NGT), and Swedish Sign Language (SSL). We propose a typology for, and report the frequency distribution of, the different types of mouth actions observed. In accordance with previous studies, we find the three languages remarkably similar — both in the types of mouth actions they use, and in how these mouth actions are distributed. We then describe how mouth actions can extend over more than one manual sign. This spreading of mouth actions is the primary focus of this paper. Based on an analysis of comparable narrative material in the three languages, we demonstrate that the direction as well as the source and goal of spreading may be language-specific.

Tweetaligheid en Alfabetisering Van Doven

1998 ◽  
Vol 59 ◽  
pp. 9-18
Author(s):  
Bob Kolsters
Keyword(s):  
Second Language ◽  
The Netherlands ◽  
Sign Language ◽  
Theoretical Framework ◽  
Deaf Children ◽  
Language Of Instruction ◽  
Educational Method ◽  
Notation System ◽  
Schools For The Deaf ◽  
Metalinguistic Knowledge

Schools for the deaf in the Netherlands are currently looking for ways of converting their current education into bilingual education. The first language of prelingual deaf children in the Netherlands is Sign Language of the Netherlands (SLN); their second language is Dutch. In the first part of the thesis, the bilingual situation of prelingual deaf children is examined with the help of a theoretical framework designed by J. Cummins and a model designed by J. Kurvers. Cummins' theoretical framework takes a thorough look at language development in different bilingual situations. Kurvers' model examines the different ways for bilingual people to obtain literacy. Both theories support the view that in order to stimulate development of the first and the second language, sign language should be the language of instruction in schools for the deaf as well as the language in which prelingual deaf children obtain literacy. Since this implies the use of a notation system for sign language in deaf education, the second part of the thesis deals with the design of a prototype of an educational method that stimulates metalinguistic knowledge with the help of such a notation system.

An Approach of Traffic Sign Recognition Algorithm on MATLAB

2014 ◽  
Vol 644-650 ◽  
pp. 3980-3983
Author(s):  
Jia Yang Li ◽  
Mei Xia Song
Keyword(s):  
Real Time ◽  
Intelligent Transportation System ◽  
Recognition System ◽  
Recognition Algorithm ◽  
Traffic Sign Recognition ◽  
Traffic Sign ◽  
Sign Recognition ◽  
Sign Detection ◽  
Traffic Sign Detection ◽  
Detection And Recognition

Traffic sign recognition system is a great important part of intelligent transportation system and advanced auxiliary driving system, and it is a key problem to improve the accuracy and real-time performance of traffic sign detection in reality.Considering to the perspective of accuracy and real-time of traffic sign detection and recognition, this article built the traffic sign detection and recognition method based on MATLAB. Finally, the paper proved the conclusion, and future traffic sign detection and recognition need to be further research topics and practical application prospect.

Sign in / Sign up

Export Citation Format

Share Document