LIMMITS’25: Multilingual Streaming TTS With Neural Codecs for Indian Languages
This work provides a summary of the Multilingual streaming TTS with neural codecs for Indian languages challenge (LIMMITS’25), organized as part of the ICASSP 2025 signal processing grand challenge. Towards this, 278 hours of TTS data in 4 Indian languages - Gujarati, Indian English, Bhojpuri, and Kannada got released. The challenge focuses on advancing research in neural codec-based and streaming TTS systems. The top teams in the challenge attained high subjective scores on naturalness and similarity, thus contributing to the progress in text-to-speech generation systems.
Authors
- Shinji Watanabe (ORCID: https://orcid.org/0000-0002-5970-8631)
- Mark Hasegawa‐Johnson (ORCID: https://orcid.org/0000-0002-5631-2893)
- Hema A. Murthy (ORCID: https://orcid.org/0000-0003-3611-6550)
- Philipp Olbrich
- Pranaw Kumar
- Sheng Zhao (ORCID: https://orcid.org/0000-0002-9624-5381)
Institutions
- Centre for Development of Advanced Computing (IN)
- University of Illinois Urbana-Champaign (US)
- Indian Institute of Technology Madras (IN)
- Deutsche Gesellschaft für Internationale Zusammenarbeit (DE)
- Microsoft Research Asia (China) (CN)
Publication Details
- Published
- 2025-03-12
- DOI
- https://doi.org/10.1109/icassp49660.2025.10890595
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Deutsche Gesellschaft für Internationale Zusammenarbeit