Developing advanced language models and conversational AI systems with special focus on Indian languages and multilingual applications
Our NLP research focuses on making AI accessible to India's diverse linguistic population while advancing the global state-of-the-art in language understanding.
Developing large language models that understand and generate text in multiple Indian languages with cultural context.
Building intelligent dialogue systems and chatbots that can engage in natural, contextual conversations.
Extracting insights from large-scale text data for business intelligence and social media analysis.
Automatically extracting structured information from unstructured text documents and web content.
We're building comprehensive NLP capabilities for India's major languages, covering over 1.2 billion speakers across the subcontinent.
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Our groundbreaking research has led to several landmark contributions in multilingual NLP and Indian language processing.
First multilingual BERT model for 12 Indian languages, achieving state-of-the-art performance on multiple NLP tasks.
Leading national initiative to democratize AI for Indian languages with open-source tools and datasets.
Advanced ASR systems supporting code-mixed speech in Indian languages with 95%+ accuracy.
Large generative language model for Indian languages with 13B parameters, supporting creative and informative text generation.
Our NLP projects focus on making AI accessible to India's diverse linguistic population while advancing global language understanding capabilities.
Large-scale multilingual BERT model supporting 12 Indian languages with state-of-the-art performance.
Advanced ASR system for Hindi-English code-mixed speech with 95%+ accuracy in real-world scenarios.
Intelligent chatbot system supporting natural conversations in multiple Indian languages.
Our NLP research focuses on multilingual systems, Indian languages, and culturally-aware language technologies.
We present IndicGPT, a 13B parameter large language model specifically designed for Indian languages, incorporating cultural context and achieving state-of-the-art performance on multilingual tasks.
A novel transformer architecture for sentiment analysis in code-mixed text, achieving 15-20% improvement over existing methods on Hindi-English and other Indian language pairs.
A comprehensive framework for multilingual question answering that leverages cross-lingual transfer learning to support low-resource Indian languages with limited training data.
The first multilingual BERT model for 12 major Indian languages, achieving state-of-the-art performance on multiple downstream NLP tasks and enabling AI for 1.2B+ speakers.
Our NLP research appears in premier computational linguistics venues
Meet our natural language processing research team.
Team component coming soon...