SIGN LANGUAGE RECOGNITION BASED ON HMM/ANN/DP

2000 ◽  
Vol 14 (05) ◽  
pp. 587-602 ◽  
Author(s):  
WEN GAO ◽  
JIYONG MA ◽  
JIANGQIN WU ◽  
CHUNLI WANG
Keyword(s):  
Sign Language ◽  
Data Stream ◽  
Recognition Performance ◽  
Combined Approach ◽  
Language Recognition ◽  
Geometrical Analysis ◽  
Sign Language Recognition ◽  
Design And Implementation ◽  
Invariant Feature ◽  
New Ideas

In this paper, a system designed for helping the deaf to communicate with others is presented. Some useful new ideas are proposed in design and implementation. An algorithm based on geometrical analysis for the purpose of extracting invariant feature to signer position is presented. An ANN–DP combined approach is employed for segmenting subwords automatically from the data stream of sign signals. To tackle the epenthesis movement problem, a DP-based method has been used to obtain the context-dependent models. Some techniques for system implementation are also given, including fast matching, frame prediction and search algorithms. The implemented system is able to recognize continuous large vocabulary Chinese Sign Language. Experiments show that proposed techniques in this paper are efficient on either recognition speed or recognition performance.

Effect of Sign-recognition Performance on the Usability of Sign-language Dictionary Search

2021 ◽  
Vol 14 (4) ◽  
pp. 1-33
Author(s):  
Saad Hassan ◽  
Oliver Alonzo ◽  
Abraham Glasser ◽  
Matt Huenerfauth
Keyword(s):  
Sign Language ◽  
Recognition Performance ◽  
The Other ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Search System ◽  
Wizard Of Oz ◽  
Sign Recognition ◽  
Technology Users ◽  
The Relationship

Advances in sign-language recognition technology have enabled researchers to investigate various methods that can assist users in searching for an unfamiliar sign in ASL using sign-recognition technology. Users can generate a query by submitting a video of themselves performing the sign they believe they encountered somewhere and obtain a list of possible matches. However, there is disagreement among developers of such technology on how to report the performance of their systems, and prior research has not examined the relationship between the performance of search technology and users’ subjective judgements for this task. We conducted three studies using a Wizard-of-Oz prototype of a webcam-based ASL dictionary search system to investigate the relationship between the performance of such a system and user judgements. We found that, in addition to the position of the desired word in a list of results, the placement of the desired word above or below the fold and the similarity of the other words in the results list affected users’ judgements of the system. We also found that metrics that incorporate the precision of the overall list correlated better with users’ judgements than did metrics currently reported in prior ASL dictionary research.

LBPV for Recognition of Sign Language at Sentence Level: An Approach Based on Symbolic Representation

2017 ◽  
Vol 26 (2) ◽  
pp. 371-385 ◽  
Author(s):  
H.S. Nagendraswamy ◽  
B.M. Chethana Kumara
Keyword(s):  
Sign Language ◽  
Recognition Performance ◽  
Recognition System ◽  
Deaf People ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Symbolic Data ◽  
Word Level ◽  
Sentence Level ◽  
Indian Sign Language

AbstractRecognition of signs made by deaf people to produce equivalent textual description for normal people to communicate with deaf people is an essential and challenging task for the pattern recognition and image processing research community. Many researchers have made an attempt to standardize and to propose a sign language recognition system. To the best our knowledge, according to the literature survey, most of the work reported has concentrated at the fingerspelling level or at the word level, and less work at the sentence level has been reported. As sign languages are very abstract, fingerspelling or word level interpretation of signs seems to be a tedious and cumbersome task. Although existing research in sign language recognition is active and extensive, it still remains a challenge to achieve accurate recognition and interpretation of signs at the sentence level. In this paper, we made an attempt to address this problem by proposing an approach that exploits the texture description technique and symbolic data analysis concept to characterize and effectively represent a sign, taking into account the intra-class variations due to different signers or the same signers at different instances of time. In order to study the efficacy of the proposed approach, extensive experiments were carried out on a considerably large database of Indian sign language created by us. The experimental results demonstrated that the proposed method has shown good recognition performance in terms of F-measure rates.

INDIAN SIGN LANGUAGE RECOGNITION SYSTEM USING OPENPOSE

2019 ◽  
Vol 7 (2) ◽  
pp. 43
Author(s):  
MALHOTRA POOJA ◽  
K. MANIAR CHIRAG ◽  
V. SANKPAL NIKHIL ◽  
R. THAKKAR HARDIK ◽  
◽  
...  
Keyword(s):  
Sign Language ◽  
Recognition System ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Indian Sign Language

STATIC DEVNAGARI SIGN LANGUAGE RECOGNITION

2016 ◽  
Vol 3 (3) ◽  
pp. 13
Author(s):  
VERMA VERSHA ◽  
PATIL SANDEEP B. ◽  
◽  
Keyword(s):  
Sign Language ◽  
Language Recognition ◽  
Sign Language Recognition
Sign in / Sign up

Export Citation Format

Share Document