  This research investigates biases in text-to-image (TTI) models for the Indic
languages widely spoken across India. It evaluates and compares the generative
performance and cultural relevance of leading TTI models in these languages
against their performance in English. Using the proposed IndicTTI benchmark, we
comprehensively assess the performance of 30 Indic languages with two
open-source diffusion models and two commercial generation APIs. The primary
objective of this benchmark is to evaluate the support for Indic languages in
these models and identify areas needing improvement. Given the linguistic
diversity of 30 languages spoken by over 1.4 billion people, this benchmark
aims to provide a detailed and insightful analysis of TTI models' effectiveness
within the Indic linguistic landscape. The data and code for the IndicTTI
benchmark can be accessed at
https://iab-rubric.org/resources/other-databases/indictti.
