| --- |
| language: |
| - tr |
| license: apache-2.0 |
| pipeline_tag: text-to-speech |
| tags: |
| - text-to-speech |
| - tts |
| - turkish |
| - flow-matching |
| - diffusion-transformer |
| - speech-synthesis |
| library_name: freyatts |
| --- |
| |
| # FreyaTTS-small |
|
|
| FreyaTTS-small is a 183M-parameter Turkish text-to-speech model, and the open-source member of the FreyaTTS family. 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](https://huggingface.co/openbmb/VoxCPM2) 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 |
|
|
| ## The FreyaTTS family |
|
|
| **FreyaTTS-small** (this model) is our compact, Apache-2.0, self-hostable model, released in full: weights, inference code, and training pipeline. |
|
|
| **FreyaTTS-large** is our production model, serving Turkish voice agents at [Freya (YC S25)](https://freyavoice.ai) with higher naturalness and expressivity. It is available commercially rather than as open weights. For access, contact us at **dev@freyavoice.ai**. |
|
|
| The model id `freyavoice/freya-tts` predates this naming and is unchanged; it refers to FreyaTTS-small. |
|
|
| ## Usage |
|
|
| ```python |
| 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](https://github.com/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](https://huggingface.co/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](https://huggingface.co/datasets/freyavoice/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-small is described in our technical report, [arXiv:2607.09530](https://arxiv.org/abs/2607.09530): |
|
|
| ```bibtex |
| @misc{pamuk2026freyattscompacttokenizerfreeflowmatching, |
| title={FreyaTTS: A Compact Tokenizer-Free Flow-Matching Transformer for Turkish-First Speech Synthesis}, |
| 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}, |
| } |
| ``` |
|
|
