Lightweight, Multi-Speaker, Multi-Lingual Indic Text-to-Speech

Abhayjeet Singh, Amala Nagireddi, G. Deekshitha, Jesuraja Bandekar, R. Roopa, Sandhya Badiger, Sathvik Udupa, Prasanta Kumar Ghosh, Hema A. Murthy, Heiga Zen, Pranaw Kumar, Kamal Kant, Amol Bole, Bira Chandra Singh, Keiichi Tokuda, Mark Hasegawa-Johnson, Philipp Olbrich

Research output: Contribution to journalConference articlepeer-review


The Lightweight, Multi-speaker, Multi-lingual Indic Text-to-Speech (LIMMITS'23) challenge is organized as part of the ICASSP 2023 signal processing grand challenge. LIMMITS'23 aims at the development of a lightweight, multi-speaker, multi-lingual Text to Speech (TTS) model using datasets in Marathi, Hindi, and Telugu. The challenge encourages the advancement of TTS in Indian Languages as well as the development of techniques involved in TTS data selection and model compression. The 3 tracks of LIMMITS'23 have provided an opportunity for various researchers and practitioners around the world to explore the state of the art in TTS research.


  • Text-to-Speech (TTS)
  • data-constrained multi-speaker
  • end-to-end
  • model compression
  • multi-lingual TTS
  • speech synthesis

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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