Citation: Sharma, P.; Tulsian, D.;
Verma, C.; Sharma, P.; Nancy, N.
Translating Speech to Indian Sign
Language Using Natural Language
Processing. Future Internet 2022, 14,
253. https://doi.org/10.3390/
fi14090253
Academic Editors: Filipe Portela and
Paolo Bellavista
Received: 18 July 2022
Accepted: 23 August 2022
Published: 25 August 2022
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future internet
Article
Translating Speech to Indian Sign Language Using Natural
Language Processing
Purushottam Sharma
1,
*, Devesh Tulsian
1
, Chaman Verma
2,
* , Pratibha Sharma
1
and Nancy Nancy
1
1
Amity School of Engineering & Technology, Amity University, Noida 201301, India
2
Department of Media and Educational Informatics, Faculty of Informatics, Eotvos Lorand University,
1053 Budapest, Hungary
* Correspondence: puru.mit2002@gmail.com(P.S.); chaman@inf.elte.hu (C.V.)
Abstract: Language plays a vital role in the communication of ideas, thoughts, and information to
others. Hearing-impaired people also understand our thoughts using a language known as sign
language. Every country has a different sign language which is based on their native language. In our
research paper, our major focus is on Indian Sign Language, which is mostly used by hearing- and
speaking-impaired communities in India. While communicating our thoughts and views with others,
one of the most essential factors is listening. What if the other party is not able to hear or grasp what
you are talking about? This situation is faced by nearly every hearing-impaired person in our society.
This led to the idea of introducing an audio to Indian Sign Language translation system which can
erase this gap in communication between hearing-impaired people and society. The system accepts
audio and text as input and matches it with the videos present in the database created by the authors.
If matched, it shows corresponding sign movements based on the grammar rules of Indian Sign
Language as output; if not, it then goes through the processes of tokenization and lemmatization.
The heart of the system is natural language processing which equips the system with tokenization,
parsing, lemmatization, and part-of-speech tagging.
Keywords: Indian Sign Language; natural language processing; tokenization; lemmatization; parsing
1. Introduction
Every country has a different sign language which is based on their native language. It
is not easy for us to speak when we know the other person is not listening, let alone hearing-
impaired. Even we with sufficient hearing abilities tend to ignore or avoid communication
with those who do not hear, and for those who cannot hear it becomes even more difficult.
Having the skill to talk to those who cannot hear can not only bridge the gap between the
two but also help in the exchange of a lot of ideas and new thoughts which could encourage
these people to contribute to the development of technology. Every mind can contribute to
making unknowns into knowns and impossible possible.
1.1. Indian Sign Language
Indian Sign Language can facilitate people to create an inclusive society in which
people with disabilities have equal chances for growth and development so that they can
live productive, safe, and dignified lives. In India’s hard-of-hearing community, Indian Sign
Language (ISL) is widely utilized. However, ISL is not utilized to teach hard-of-hearing
students in deaf schools. Teacher education programs do not train teachers to use ISL
in their classrooms. Sign language is not included in any of the teaching materials. The
parents of hard-of-hearing children are often unaware of sign language’s value in bridging
communication gaps. ISL interpreters are in high demand at institutes and other locations
where hard-of-hearing and hearing individuals communicate, yet India only has about
300 licensed interpreters.
ISL aims to conquer the following points:
Future Internet 2022, 14, 253. https://doi.org/10.3390/fi14090253 https://www.mdpi.com/journal/futureinternet