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cs.CL2026
Vimarsha: Faithful ASR Evaluation for Indian Languages with Demographic Diversity, In-the-Wild Audio and Spelling Variations
Kaushal Santosh Bhogale, Srija Anand, Sadakopa Ramakrishnan Thothathiri +3
Evaluation benchmarks for Indian language automatic speech recognition (ASR) suffer from two systematic biases: optimistic scores from clean, controlled audio conditions, and pessi…
cs.CL2026
Preferences of a Voice-First Nation: Large-Scale Pairwise Evaluation and Preference Analysis for TTS in Indian Languages
Srija Anand, Ashwin Sankar, Ishvinder Sethi +10
Crowdsourced pairwise evaluation has emerged as a scalable approach for assessing foundation models. However, applying it to Text to Speech(TTS) introduces high variance due to lin…
cs.CL2026
Afri-MCQA: Multimodal Cultural Question Answering for African Languages
Atnafu Lambebo Tonja, Srija Anand, Emilio Villa-Cueva +16
Africa is home to over one-third of the world's languages, yet remains underrepresented in AI research. We introduce Afri-MCQA, the first Multilingual Cultural Question-Answering b…