BHASHINI AI Platform Advances India's Language Inclusion with AI-Powered Translation

The BHASHINI national language AI platform has evolved from rule-based to AI-powered systems to provide inclusive language services across India. It emphasizes a collaborative ecosystem involving government, academia, civil society, and industry to co-develop language technology. The platform aims for comprehensive translation across all 22 scheduled languages, including non-scheduled languages and dialects, ensuring no language community is left behind. Initiatives like the Dataset Onboarding Supporting Team (DOST) support the systematic integration of high-value datasets to strengthen the AI language infrastructure.

Key Points: BHASHINI AI Drives India's Language Inclusion & Translation Mission

  • AI-powered language services for all citizens
  • Covers 22 scheduled languages and dialects
  • Collaborative ecosystem with shared ownership
  • Focus on dataset creation and community participation
2 min read

BHASHINI provides AI language services to citizens towards full 'societal inclusivity'

India's BHASHINI AI platform transitions to AI-powered engines, offering translation across 22+ languages to achieve full societal inclusivity and digital access.

"Samudaye is about building a living ecosystem... co-developing language technology together, with shared value and responsibility. - Amitabh Nag"

New Delhi, Jan 14

National language AI platform BHASHINI has moved from rule-based systems to AI-powered inclusive engines, providing language services to all citizens and advancing towards full societal inclusivity, according to senior government officials.

The Digital India BHASHINI Division at IT Ministry organised 'BHASHINI Samudaye: Strengthening India's Language AI Ecosystem' here in collaboration with Wadhwani AI.

According to a ministry statement, the event represented a significant step in consolidating India's language AI ecosystem through collaborative engagement, participatory governance, and shared ownership of public digital infrastructure.

"Samudaye is about building a living ecosystem - data creators, annotators, translators, developers, users, and governments - co-developing language technology together, with shared value and responsibility," said Amitabh Nag, CEO, Digital India BHASHINI Division (MeitY).

Professor Girish Nath Jha, School of Sanskrit and Indic Studies, Jawaharlal Nehru University, said that "BHASHINI demonstrates the importance of structured dataset creation, domain-specific accuracy, and community participation. This approach is critical for developing AI systems that reflect India's linguistic diversity and societal needs."

The discussion highlighted the collaborative role of government agencies, academic institutions, civil society organisations, and industry stakeholders in advancing language AI initiatives across India.

According to the Ministry, the workshop convened language experts, academic institutions, civil society organisations, and data practitioners to examine use cases and identify pathways for co-creating, governing, and scaling language AI solutions under the National Language Translation Mission (NLTM).

"The success of BHASHINI lies in its comprehensive approach to translation: covering sentence-level, discourse-level, and conversational translation across all 22 scheduled languages, including non-scheduled languages and dialects," said Shobha L., Member Research Staff, AU-KBC Research Centre.

Addressing the challenges in Dravidian languages, which often lack Sanskrit equivalents, requires expanded datasets and continued collaboration. BHASHINI's work ensures no language is left behind, she added.

BHASHINI, in collaboration with the Gates Foundation and implemented by Civic Data Lab, launched the Dataset Onboarding Supporting Team (DOST) to support the systematic identification, preparation, and onboarding of high-value datasets into BHASHINI and AI Kosh.

- IANS

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Reader Comments

S
Shreya B
The focus on Dravidian languages and dialects is crucial. Often, tech solutions are built for major languages and others are an afterthought. Hope this leads to better access to education and healthcare information in languages like Telugu and Kannada in rural areas.
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Rahul R
While the intent is good, I hope the execution is solid. AI translation for Indian languages is tricky due to context, idioms, and regional variations. The success will depend entirely on the quality and diversity of the datasets. Fingers crossed!
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Priyanka N
This collaborative model with universities and civil society is the right way to build public tech. It shouldn't just be a top-down government project. Including actual users and language experts will make BHASHINI more accurate and useful for the common person.
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David E
As an expat working here, I'm impressed. India's linguistic diversity is a huge challenge for tech adoption. If BHASHINI works, it could be a model for other multilingual nations. The focus on "conversational translation" is key for real-world use.
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Meera T
Hope this leads to more content creation in Indian languages online. Most of the useful knowledge is locked in English. If my parents can search for recipes or medical advice in Gujarati using voice commands, that would be true empowerment.
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Vikram M

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