freyavoice/Freya-TTS

FreyaTTS

FreyaTTS is a 183M-parameter Turkish text-to-speech model. It is tokenizer-free at the character level (92 symbols, no phonemizer or G2P) and generates speech with a non-autoregressive conditional flow-matching DiT in the frozen AudioVAE2 latent space (25 Hz, 64-dim latents, 16 kHz encode / 48 kHz decode). Output is 48 kHz mono.

• Repository: https://github.com/freyavoiceai/FreyaTTS
• Eval set: https://huggingface.co/datasets/freyavoice/freya-tr-eval
• License: Apache-2.0

Usage

from freyatts import FreyaTTS

tts = FreyaTTS.from_pretrained("freyavoice/freya-tts", device="cuda")
wav = tts.synthesize("Merhaba, size nasıl yardımcı olabilirim?")   # np.float32, 48 kHz
tts.save_wav(wav, "output.wav")

Clone freyavoiceai/FreyaTTS and install requirements.txt.

Model details

• Architecture: conditional flow-matching diffusion transformer, non-autoregressive, 32-step Euler ODE, no CFG
• Parameters: 183.2M
• Input: character-level Turkish, 92-symbol vocabulary
• Latent space: frozen AudioVAE2 (Apache-2.0, openbmb/VoxCPM2), 64-dim at 25 Hz, decodes to 48 kHz
• Training: from scratch on Turkish speech; pretraining followed by SFT stage 1/2 (voice lock, short-utterance coverage)
• Voice: single target speaker, no cloning

Evaluation

On Freya-TR-Eval: WER 8.0% / CER 3.0%, ranking 3rd of 7 among open sub-1B Turkish TTS models, ahead of XTTS-v2 (11.1% WER) and F5-TTS (24.3% WER).

Speed

• RTX 4090: RTF 0.10-0.11, TTFT ~0.5 s, 1.5 GB VRAM, 9.4 audio-s/s at concurrency 4
• About 3.2x faster RTF and 3.7x less VRAM than the 2B VoxCPM2
• Apple M3 laptop CPU: RTF 0.70 (fp32); ~0.12 end to end via Core ML on Apple silicon

Citation

FreyaTTS is described in our technical report, arXiv:2607.09530:

@misc{pamuk2026freyattstechnicalreport,
      title={FreyaTTS Technical Report}, 
      author={Ahmet Erdem Pamuk and Ömer Yentür and Ahmet Tunga Bayrak and Yavuz Alp Sencer Öztürk and Mustafa Yavuz},
      year={2026},
      eprint={2607.09530},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2607.09530}, 
}