  We release Rasa, the first multilingual expressive TTS dataset for any Indian
language, which contains 10 hours of neutral speech and 1-3 hours of expressive
speech for each of the 6 Ekman emotions covering 3 languages: Assamese,
Bengali, & Tamil. Our ablation studies reveal that just 1 hour of neutral and
30 minutes of expressive data can yield a Fair system as indicated by MUSHRA
scores. Increasing neutral data to 10 hours, with minimal expressive data,
significantly enhances expressiveness. This offers a practical recipe for
resource-constrained languages, prioritizing easily obtainable neutral data
alongside smaller amounts of expressive data. We show the importance of
syllabically balanced data and pooling emotions to enhance expressiveness. We
also highlight challenges in generating specific emotions, e.g., fear and
surprise.
