IndicTalk: A Large-Scale Persona-Based Multilingual Conversational Corpus for Indic Languages

Researchers at LingoIITGN have released IndicTalk, a multilingual code-mixed conversational corpus comprising over 13,28,604 multi-turn conversations across 18 language varieties covering 9 Indic languages, generated through an automated pipeline combining news grounding, persona-conditioned dialogue generation, and quality validation. The dataset, available on Hugging Face, aims to support the development of conversational AI for underrepresented Indic languages.

arXiv:2607.23242v1 Announce Type: new Abstract: Large Language Models LLMs have transformed conversational AI, yet high-quality multilingual code-mixed dialogue resources remain scarce, particularly for Indic languages where speakers naturally alternate between English and their native language in both native-script and Romanized forms. We present IndicTalk, one of the largest multilingual Indic code-mixed conversational corpora, comprising over 13,28,604 event-grounded multi-turn conversations across 18 language varieties covering 9 Indic languages. The corpus is generated through a fully automated pipeline that combines real-world news grounding, persona-conditioned dialogue generation using multilingual LLMs, and automatic quality validation. Extensive linguistic, automatic, and human evaluations demonstrate that IndicTalk produces fluent, coherent, and naturally code-mixed conversations across both script variants. We will release IndicTalk to support the development and evaluation of multilingual conversational AI for underrepresented Indic languages. The dataset is available at: https://huggingface.co/datasets/LingoIITGN/IndicTalk .