3 papers
cs.CL2024
IndicVoices-R: Unlocking a Massive Multilingual Multi-speaker Speech Corpus for Scaling Indian TTS
Ashwin Sankar, Srija Anand, Praveen Srinivasa Varadhan +7
Recent advancements in text-to-speech (TTS) synthesis show that large-scale models trained with extensive web data produce highly natural-sounding output. However, such data is sca…
cs.CL2024
Rasa: Building Expressive Speech Synthesis Systems for Indian Languages in Low-resource Settings
Praveen Srinivasa Varadhan, Ashwin Sankar, Giri Raju +1
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…
cs.CL2024
Enhancing Out-of-Vocabulary Performance of Indian TTS Systems for Practical Applications through Low-Effort Data Strategies
Srija Anand, Praveen Srinivasa Varadhan, Ashwin Sankar +2
Publicly available TTS datasets for low-resource languages like Hindi and Tamil typically contain 10-20 hours of data, leading to poor vocabulary coverage. This limitation becomes…