India Turns to AI to Capture its 121 Languages: A Technological Revolution in Language Preservation

In recent weeks, an innovative project unfolded in Karnataka, a southwestern Indian state, where villagers actively participated in a pioneering initiative. They engaged with an application, articulating numerous sentences in Kannada, their mother tongue.

This endeavor is crucial to India's ambitious plan to develop its first AI-driven chatbot specifically for Tuberculosis-related communication. Kannada, spoken by over 40 million people, is one of India's 22 officially recognized languages and is among the more than 121 languages spoken by at least 10,000 individuals in this densely populated country.

Despite this linguistic richness, only a handful of these languages benefit from advancements in Natural Language Processing (NLP). This AI domain empowers computers to interpret and process human language in text and speech forms.

Native Kannada Language and Beyond: AI's Role in Language Digitization

The project focuses on local languages like Kannada, spoken predominantly in the southwestern Indian state of Karnataka. Using AI-led language translation systems, the aim is to create expansive language datasets that can understand and translate not just Kannada but various Indian languages. This initiative is a testament to India's dedication to preserving major languages and giving voice to local and regional dialects.

Bhashini: The Cornerstone of India's AI Language Project

This initiative's heart is 'Bhashini', an AI-led platform developed by Microsoft Research India and the Indian Language Technology Lab. Bhashini is designed to process natural language, making it a pivotal tool in building language datasets through advanced natural language processing (NLP) techniques. Its role in understanding and translating different Indian languages is crucial for creating AI tools that can accurately interpret and process speech data.

The Future of Indian Languages: Building Datasets and AI Models

The task of building language datasets for 121 languages is monumental. It involves collecting texts and labeling images in various languages, an essential process for training generative AI models. Based on large language models, these models will be able to understand and translate spoken words in different Indian languages, a feat that would have seemed impossible just a few years ago.

Citizen Participation: Contributing to Language Preservation

An interesting aspect of this project is its open invitation to citizens to contribute sentences and speech data in their native languages. This approach accelerates the data collection process and ensures that the language models developed are diverse and representative of the spoken words across different regions.

Challenges and Opportunities: A Few Weeks into the Journey

While the project is in its early stages, with just a few weeks since its inception, its potential is enormous. Capturing the essence of India's linguistic diversity through AI is a challenge that comes with its own set of obstacles. However, the opportunity to preserve languages that might otherwise be lost to time is a powerful motivator.

Conclusion: India's Leap into AI-Powered Language Preservation

As India turns to AI to capture its 121 languages, it marks a significant leap in using technology for cultural preservation. By harnessing the power of natural language processing and AI models, this initiative stands as a beacon of hope for preserving linguistic diversity, not just in India but worldwide.

It's a journey that combines technology with cultural heritage, ensuring that the voices of hundreds of millions are heard and preserved for future generations.