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
- Included in the official repository of VITS: https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechSynthesis/FastPitch
- Our repository on finetuning various TTS models for the Romanian language: https://gitlab.com/opentts_ragman/OpenTTS
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}}