5 papers · 1 filter
Rethinking MUSHRA: Addressing Modern Challenges in Text-to-Speech Evaluation
Praveen Srinivasa Varadhan, Amogh Gulati, Ashwin Sankar +8
Despite rapid advancements in TTS models, a consistent and robust human evaluation framework is still lacking. For example, MOS tests fail to differentiate between similar models,…
Towards Building Large Scale Datasets and State-of-the-Art Automatic Speech Translation Systems for 14 Indian Languages
Ashwin Sankar, Sparsh Jain, Nikhil Narasimhan +6
Speech translation for Indian languages remains a challenging task due to the scarcity of large-scale, publicly available datasets that capture the linguistic diversity and domain…
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…
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…
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…