Automated 3D sign language caption generation for video

Nayan Mehta, Suraj Pai, Sanjay Singh

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


Efforts to make online media accessible to a regional audience have picked up pace in recent years with multilingual captioning and keyboards. However, techniques to extend this access to people with hearing loss are limited. Further, owing to a lack of structure in the education of hearing impaired and regional differences, the issue of standardization of Indian Sign Language (ISL) has been left unaddressed, forcing educators to rely on the local language to support the ISL structure, thereby creating an array of correlations for each object, hindering the language building skills of a student. This paper aims to present a useful technology that can be used to leverage online resources and make them accessible to the hearing-impaired community in their primary mode of communication. Our tool presents an avenue for the early development of language learning and communication skills essential for the education of children with a profound hearing loss. With the proposed technology, we aim to provide a standardized teaching and learning medium to a classroom setting that can utilize and promote ISL. The goals of our proposed system involve reducing the burden of teachers to act as a valuable teaching aid. The system allows for easy translation of any online video and correlation with ISL captioning using a 3D cartoonish avatar aimed to reinforce classroom concepts during the critical period. First, the video gets converted to text via subtitles and speech processing methods. The generated text is understood through NLP algorithms and then mapped to avatar captions which are then rendered to form a cohesive video alongside the original content. We validated our results through a 6-month period and a consequent 2-month study, where we recorded a 37% and 70% increase in performance of students taught using Sign captioned videos against student taught with English captioned videos. We also recorded a 73.08% increase in vocabulary acquisition through signed aided videos.

Original languageEnglish
JournalUniversal Access in the Information Society
Publication statusPublished - 01-11-2020

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Networks and Communications


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