Romanian TTS Model (Finetuned)

This is a FastPitch model finetuned for the Romanian language. It was trained (from scratch) on the SWARA dataset and finetuned on specific speaker samples (BEA/SGS).

Model Details

  • Architecture: FastPitch
  • Language: Romanian (ro)
  • Base Dataset: The SWARA Speech Corpus (18k samples)
  • Base Model: trained on 16 speakers (includes both male & female voices, balanced data). The base model components can be found in the 'swara' directory.
  • Finetuning: finetuned on 2 speakers (bas and sgs). Their checkpoints can be found in the 'bas' and 'sgs' directories.
  • Sample rate: 22050Hz

Usage instructions

Citation

If you use this model, please cite the original FastPitch paper and the SWARA dataset:

@INPROCEEDINGS{fastpitch,
  author={Łańcucki, Adrian},
  booktitle={Proc. of ICASSP}, 
  title={{Fastpitch: Parallel Text-to-Speech with Pitch Prediction}}, 
  year={2021},
  volume={},
  number={},
  pages={6588-6592},
  keywords={Frequency synthesizers;Frequency modulation;Conferences;Semantics;Predictive models;Real-time systems;Acoustics;text-to-speech;speech synthesis;fundamental frequency},
  doi={10.1109/ICASSP39728.2021.9413889}}

@inproceedings{stan_sped2017,
  author = {Stan, Adriana and Dinescu, Florina and Tiple, Cristina and Meza, Serban and Orza, Bogdan and Chirila, Magdalena and Giurgiu, Mircea},
  title = {{The SWARA Speech Corpus: A Large Parallel Romanian Read Speech Dataset}},
  year = 2017,
  address = {Bucharest, Romania},
  booktitle = {{Proceedings of the 9th Conference on Speech Technology and Human-Computer Dialogue (SpeD)}},
  month = {July, 6-9},
}

If you use this specific finetuned checkpoint in your work, please cite it as follows:

@ARTICLE{11269795,
  author={Răgman, Teodora and Bogdan Stânea, Adrian and Cucu, Horia and Stan, Adriana},
  journal={IEEE Access}, 
  title={How Open Is Open TTS? A Practical Evaluation of Open Source TTS Tools}, 
  year={2025},
  volume={13},
  number={},
  pages={203415-203428},
  keywords={Computer architecture;Training;Text to speech;Spectrogram;Decoding;Computational modeling;Codecs;Predictive models;Acoustics;Low latency communication;Speech synthesis;open tools;evaluation;computational requirements;TTS adaptation;text-to-speech;objective measures;listening test;Romanian},
  doi={10.1109/ACCESS.2025.3637322}}
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