mlsanityData to 13 Oct 2026

MunTTS: A Text-to-Speech System for Mundari

arXiv 2401.15579 ↗First posted 28 Jan 2024cs.CL cs.SD eess.AScited by 1

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Abstract (arXiv)

We present MunTTS, an end-to-end text-to-speech (TTS) system specifically for Mundari, a low-resource Indian language of the Austo-Asiatic family. Our work addresses the gap in linguistic technology for underrepresented languages by collecting and processing data to build a speech synthesis system. We begin our study by gathering a substantial dataset of Mundari text and speech and train end-to-end speech models. We also delve into the methods used for training our models, ensuring they are efficient and effective despite the data constraints. We evaluate our system with native speakers and objective metrics, demonstrating its potential as a tool for preserving and promoting the Mundari language in the digital age.

Key facts. Cited by 1 paper in the map (data through 13 Oct 2026). Builds on 11 of its 23 references that are in the map. First posted on arXiv 28 Jan 2024.

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References · 11

  1. 2016WaveNet: A Generative Model for Raw Audiocited by 1,717
  2. 2017Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictionscited by 803
  3. 2020FastSpeech 2: Fast and High-Quality End-to-End Text to Speechcited by 715
  4. 2021Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speechcited by 559
  5. 2017Tacotron: Towards End-to-End Speech Synthesiscited by 489
  6. 2023Scaling Speech Technology to 1,000+ Languagescited by 402
  7. 2019Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogramcited by 339
  8. 2021A Survey on Neural Speech Synthesiscited by 182
  9. 2023IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languagescited by 149
  10. 2022Towards Building Text-To-Speech Systems for the Next Billion Userscited by 27
  11. 2020Generic Indic Text-to-speech Synthesisers with Rapid Adaptation in an End-to-end Frameworkcited by 9

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