Engine totranslate textbooks and learning material in Hindi in one-sixth the time and in due course, textbooks in all domains can be taken up
On September 14, which is celebrated as Hindi Divas every year, the Indian Institute of Technology (IIT) Bombay launched Project Udaan, an AI-based translation ecosystem to translate engineering textbooks and learning materials in Hindi in one-sixth the time it would take for a team consisting of domain and linguistic experts working manually. In due course, textbooks in all domains can be taken up.
This project has been developed by Ganesh Ramakrishnan, the institute chair professor, department of computer science and engineering at IIT Bombay and his team.
The launch took place during a virtual event, which saw Krishnaswamy Vijay Raghavan, principal scientific advisor to the Government of India as its chief guest. Project Udaan is a donation-based project and an end-to-end ecosystem, which translates scientific and technical content from English to Hindi and all other Indian languages.
Seven years ago, Ramakrishnan and his team decided to come up with the project owing to the wide gap they saw in the availability of technical knowledge in Hindi and other Indian languages. The Indian Constitution and now NEP 2020 requires every state and local authority within the state to provide adequate facilities for instruction in the mother-tongue at the primary stage of education to children belonging to linguistic minority groups.
The need of the hour is to cater to 80% of the Indian population by making scientific and technical knowledge available in Indian languages and thus, Project Udaan came into being.
The evolution, progress and capabilities of Ramakrishnan and his team’s end-to-end translation ecosystem has coincided with the implementation of the New Education Policy based initiative to introduce higher education through Indian languages. Through donations, the team aims to continue its work on Project Udaan, and complete its target to translate 500 engineering texts in Hindi in one year and in 15 Indian languages in three years.
“We are happy to state that by deploying our AI-based translation engine, we are now able to translate a technical book in less than one-sixth the time it would take for a team consisting of domain and linguistic experts working manually. In due course, as our AI and ML engine learns with every page and every book being edited in each domain, we expect to achieve a much shorter turnaround time,” said Ramakrishnan.
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