Pattern recognition and synthesis for sign language translation system

Ohki, Masaru; Sagawa, Hirohiko; Sakiyama, Tomoko; Oohira, Eiji; Ikeda, Hisako; Fujisawa, Hiromichi

doi:10.1145/191028.191030

Cited by 7 publications

(3 citation statements)

References 1 publication

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“…• Translation system: Ohki et al [103] describe a system that used Data glove input for Japanese Sign Language (JSL) recognition and used avatars for signing responses. The system was used for an automatic resident card delivery machine, which has similar interactions to that of an ATM.…”

Section: Applications Of Automatic Sign Language Recognitionmentioning

confidence: 99%

Improving the efficacy of automated sign language practice tools

Brashear

2007

SIGACCESS Access. Comput.

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CopyCat is an America Sign Language (ASL) game, which uses gesture recognition technology to help young Deaf children practice ASL skills. Our database of signing samples was collected from user studies of Deaf children playing a Wizard of Oz version of the game at the Atlanta Area School for the Deaf. We have created an automatic sign language recognition system for the game. We believe that we can improve the accuracy of this system by characterizing and modeling disfluencies found in the children's signing.

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Section: Applications Of Automatic Sign Language Recognitionmentioning

confidence: 99%

Improving the efficacy of automated sign language practice tools

Brashear

2007

SIGACCESS Access. Comput.

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“…Sign language has not only been examined as a means of conveying information from the computer to the user, but it has also been researched as a means for the user to convey information into the computer via a DataGlove. The DataGlove allows hand motions to be interpreted and translated into text [61]. Regardless of whether face and gesture systems serve as the input to a computer or output from a computer, they enable information access to users who may not typically be able to use computers using traditional input/output devices.…”

Section: Representative Sample Of Technologies and Strategies For Accmentioning

confidence: 99%

A review and reappraisal of information technologies within a conceptual framework for individuals with disabilities

Jacko

Vitense

2001

UAIS

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With over thirty million individuals with disabilities being reported in the United States, and with information systems permeating nearly every aspect of society, there is a growing urgency to ensure that everyone has equal access to technology. To render information technologies universally accessible, researchers must have at their disposal an accurate and reliable user model. Through the use of the conceptual framework presented here, accurate assumptions can be generated from knowledge of an individual's impairments, and functional abilities to influence the creation of a user profile. Ultimately, user profiles serve as a vital attribute of user models applied to the design of technology in an effort to achieve universal access.

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“…Most of them applied using speech recognition [7], select a picture and creates a text [5], or translates oral language into sign language which can be proceed to an image [6], etc. Research on support recognition of sign language recognition is also done.…”

Section: Introductionmentioning

confidence: 99%

A remote conversation support system for deaf-mute persons based on bimanual gestures recognition using finger-worn devices

Kuroki¹,

Zhou²,

Cheng

et al. 2015

2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)

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Communication between deaf-mute persons and normal people is very difficult when the subjects are out of the objects' view side, or vice verse. This paper presents a hand gesture recognition system using Magic Ring (a ring-shape wearable device) instead of data glove or camera to translate the predefined hand gestures into Japanese and to accomplish remote transmission of the information/command between user groups. The hand gestures are defined based on simplified Japanese sign language. The KNN method is adopted to the pattern recognition according to the bimanual sensing data. To improve the recognition rate, three most similar pre-reserved gestures and similarity are recorded, and Euclidean distance of feature values is used to estimate the gesture similarity. According to the user survey, the system shows good usability and most of the users would like to use such a system. Moreover, in the userdependent setting, the bimanual accuracy is 85.2%, which is our performance 7.8% by using only right hand.

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Pattern recognition and synthesis for sign language translation system

Cited by 7 publications

References 1 publication

Improving the efficacy of automated sign language practice tools

Improving the efficacy of automated sign language practice tools

A review and reappraisal of information technologies within a conceptual framework for individuals with disabilities

A remote conversation support system for deaf-mute persons based on bimanual gestures recognition using finger-worn devices

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