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Tanmoy Bhattacharya
Co o rd i n a to r
Eq u a l O p p o r tu n i ty Ce l l
Un i vers i t y o f De l h i
t an mo y1@g mai l . Co m
ICT for PwDs:with Special Reference to
Indian Sign Language
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Equal Opportunity Cell: University of Delhi
Access Audit: 140 digitised reportsServices: Reading, Braille printing, e-text
conversion, recording for talking books, Transportation, ICT lab, assistive devices, Sign Language Interpreters
Events: Inclusive Chess tournament, Sports events, Cultural Festival, National Disability Conference; Awareness Workshops in Colleges and Schools
Skills Development Courses: English Communication, ICT for Blind and Mobility Impaired, News Reading and Cinematography, Sign Language Interpretation A, B and C Levels, Disability and Human Rights. Short-term Summer Courses on Computer literacy
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On Sign Language
Sign languages create representations in the space in front of the signer (Signing Space)
Due to the importance of vision, signed languages take advantage of spatial representations (he, she, it, etc.)
The linguistic uniqueness of sign localisation is beyond doubt
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The Signing Space
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Time in Indian Sign Language: An Example
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SL Technology
Text/ Speech-to-Sign Voice recognition module (Speech Recogniser) Conversion of sentence to fit the grammar of sign language
(Inter-Language Translator) 3D Avatar Animation Module
Sign-to-Text/ Speech Sign Recognition: Video Signal input to large vocabulary
speech recognition database Automatic machine translation system to create a spoken
language translationProblems: Simultaneousness; 3D body-centred Signing
Space; Sub-word units
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Status of SL Recognition Systems
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“Today’s Sign Language recognition is at about the stage where speech recognition was 20 years ago”
-- Thad Starner, Head of the Contextual Computing Group at the Georgia Institute of Technology
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Challenges to ICT for Deaf
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The major barrier in using ICT for the Deaf is the assumption that English/ Hindi/ State language is their first language – their capabilities are often measured against understanding the written word
Most effective ICT for the Deaf is visual rather than based on the written word or sound
Text messages are limiting since it doesn’t convey emotions, voice inflections or body language (similarly Text-Speech systems)
The smart phones with front-facing cameras for videoconferencing can be used for video chat but are too much of a bandwidth hog
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Applications Currently Available or Under Research
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Video Chat Softwares Online Dictionaries Speech-Signal Translators Automated SL Generation
System Smart Phone Applications
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Video Chat Software
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ASL On-line Dictionary
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SiSi (Say It Sign It)
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IBM Research, Hursely, UK, 2007Voice-Text-Sign
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NHK Science & Technology Research laboratories, Japan
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Smart Phone Application
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Existing Infrastructure
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Schools, Common Service Centres, Primary Health Centres, Panchayats, Women’s Self Help Groups (SHGs), already covered under various USOF programmes
Rural and Remote Areas Mobile Services of USOF: 500 districts in 27 states
Rural Broadband Scheme: 8,61,459 Broadband connections; Scheme for Intra-District Networks on Bandwith Sharing with 2.5 Gb capacity
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Future Directions
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Development of the ISL sign setDevelopment of software for converting Hindi/ regional
language words to ISL through online dictionary Interactive learning software using the NBT book series
for shapes, measures, colours, time, money for 2-3 year olds; newspaper and adult education for Deaf adults
Send video over both 3G and Wi-Fi networks at a very low bit rate
Optimisation of compressed video signals by increasing image quality around the face and hands to bring data rate down
Motion detection to identify whether a person is signing or not for extending battery life
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Contact
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Tanmoy Bhattacharya
CoordinatorEqual Opportunity Cell
DU-NTPC Foundation ICT Training CentreTutorial Building, Arts Faculty
University of DelhiDelhi 110007
Phone: 011-27662602 (Office)Email: [email protected]; [email protected]
Website: http://eoc.du.ac.in
