FreyaTTS: A Compact Tokenizer-Free Flow-Matching Transformer for Turkish-First Speech Synthesis
We introduce Freya-TTS, a compact, tokenizer-free, Turkish-first text-to-speech model designed for highly reliable and efficient conversational synthesis. Freya-TTS is a 183.2M-parameter non-autoregressive conditional flow-matching Diffusion Transformer (DiT) that operates in the continuous latent space of the frozen AudioVAE2 (16 kHz encode, 48 kHz decode), allowing the model to focus its capacity on text-to-latent mapping while inheriting high-quality 48 kHz reconstruction. We advance the framework along three key dimensions: (1) rule-free end-to-end modeling from a 92-symbol Turkish character vocabulary without a phonemizer, grapheme-to-phoneme frontend, or discrete speech tokenizer, w...
| Authors | Ahmet Erdem Pamuk, Ömer Yentür, Ahmet Tunga Bayrak et al. |
|---|---|
| Primary category | cs.CL |
| Published | 10 July 2026 |
| Last updated at source | 22 July 2026 |
Connected in the knowledge graph
- erayack/freya-tts-mlx-evalDataset · cited by
- freyavoice/freya-tr-evalDataset · cited by
- freyavoice/Freya-TTSModel · cited by
Models and datasets referencing this paper
- freyavoice/Freya-TTSModel
- freyavoice/freya-tr-evalDataset
- erayack/freya-tts-mlx-evalDataset
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