Abstract
Sign language, a language used by Deaf community, is a fully visual language with its own grammar. The Deaf people find it very difficult to express their feelings to the other people, since the other people lack the knowledge of the sign language used by the Deaf community. Due to the differences in vocabulary and grammar of the sign languages, complete adoption of methods used for other international sign languages is not possible for Indian Sign Language (ISL) recognition. It is difficult to handle continuous sign language sentence recognition and translation into text as no large video dataset for ISL sentences is available. INSIGNVID - the first Indian Sign Language video dataset has been proposed and with this dataset as input, a novel approach is presented that converts video of ISL sentence in appropriate English sentence using transfer learning. The proposed approach gives promising results on our dataset with MobilNetV2 as pretrained model.
Highlights
Sign language is primary language for Deaf people to communicate with each other as well as with hearing people
This section introduces dataset INSIGNVID, containing set of video sequences of Indian Sign Language (ISL) sentences using word signs released by Indian Sign Language Research and Training Centre (ISLRTC)
It is essential to work on continuous ISL sentence recognition, as it is primary language used by Deaf community to communicate with other people
Summary
Sign language is primary language for Deaf people to communicate with each other as well as with hearing people. Understanding sign language is difficult for hearing person, that is why human interpreters are required in emergency situations They provide interpreting service that is easy-to-use but it has major limitations because India has only around 300 certified interpreters [2]. The hearing person will understand the message that a Deaf want to convey Such an approach should be the best alternative to the human interpreter in case of emergency situations or even to access the services in local community. One of the ways for dealing with the problem of limited dataset size is called data augmentation [15] This approach can be used on input videos for Indian sign language recognition to make dataset inflated.
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