| title | IndicTalk: A Large-Scale Persona-Based Multilingual Conversational Corpus for Indic Languages |
|---|---|
| authors | Sahil Deepak Gawande, Mayank Singh |
| date | 2026-07-25 |
| venue | arXiv (preprint, not peer reviewed) |
| id | arXiv:2607.23242 |
| affiliation | Lingo Research Group |
| upvotes | 3 (Hugging Face Daily Papers, 2026-11-01) |
| links | abs pdf hf |
| 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 . |
cite
@misc{gawande2026indictalk,
title={IndicTalk: A Large-Scale Persona-Based Multilingual Conversational Corpus for Indic Languages},
author={Sahil Deepak Gawande and Mayank Singh},
year={2026},
eprint={2607.23242},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2607.23242}
}