Papers by Anubha Gupta
MORPHOGEN: A Multilingual Benchmark for Evaluating Gender-Aware Morphological Generation (2026.acl-long)
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| Challenge: | In morphologically rich languages, gender influences verb conjugation, pronouns, and even first-person constructions with explicit and implicit mentions of gender. |
| Approach: | They propose a morphologically grounded large-scale benchmark dataset for evaluating gender-aware generation in three typologically diverse grammatically gendered languages: French, Arabic, and Hindi. |
| Outcome: | The proposed dataset compares 15 popular multilingual large language models on their ability to handle morphological gender and morphology agreement. |
IndicSynth: A Large-Scale Multilingual Synthetic Speech Dataset for Low-Resource Indian Languages (2025.acl-long)
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| Challenge: | Recent advances in synthetic speech generation technology have enabled the generation of high-quality synthetic (fake) speech that emulates human voices. |
| Approach: | They propose a dataset that contains 4,000 hours of synthetic speech from 989 target speakers for 12 low-resourced Indian languages. |
| Outcome: | The proposed dataset contains 4,000 hours of synthetic speech from 989 target speakers, including 456 females and 533 males for 12 low-resourced Indian languages. |