README.md

---
license: cc-by-nc-4.0
datasets:
- amphion/Emilia-Dataset
- mozilla-foundation/common_voice_12_0
language:
- el
- en
base_model:
- SWivid/F5-TTS
pipeline_tag: text-to-speech
---

# F5-TTS-Greek

## F5-TTS model finetuned to speak Greek

(This work is under development and is in beta version.)

Finetuned on Greek speech datasets and a small part of Emilia-EN dataset to prevent catastrophic forgetting of English.

Model can generate Greek text with Greek reference speech, English text with English reference speech, and mix of Greek and English (quality here needs improvement, and many runs might be needed to get good results).

#### NOTE: For Greek text, there is an issue with uppercase characters and it will skip them, so only use lowercase characters!

#### NOTE 2: Because the training data contained short reference audios, the best length should be around 6-9 seconds instead of the 15 in the original model.

## Datasets used:

- Common Voice 12.0 (All Greek Splits) (https://huggingface.co/datasets/mozilla-foundation/common_voice_12_0)
- Greek Single Speaker Speech Dataset (https://www.kaggle.com/datasets/bryanpark/greek-single-speaker-speech-dataset)
- Small part of Emilia Dataset (https://huggingface.co/datasets/amphion/Emilia-Dataset) (EN-B000049.tar)

## Training

Training was done in a single RTX 3090.

After some manual evaluation, these two checkpoints produced the best results:
- 225K steps ([model_225000.safetensors](https://huggingface.co/PetrosStav/F5-TTS-Greek/resolve/main/model_225000.safetensors?download=true))
- 325K steps ([model_325000.safetensors](https://huggingface.co/PetrosStav/F5-TTS-Greek/resolve/main/model_325000.safetensors?download=true))

## How to use

With the [dcd9a19 commit](https://github.com/SWivid/F5-TTS/commit/dcd9a19889147481d0a6f4b34505cdf75a1f3b90) of the main github project page, now you can directly use custom models in the `infer_gradio` page:

![image/png](https://cdn-uploads.huggingface.co/production/uploads/62d01102fb896639b296b9d3/wd5GEqB86Ny7ZM_L830Af.png)

You can either download the models and use the local paths or use the hf paths of this repo directly:
- hf://PetrosStav/F5-TTS-Greek/model_325000.safetensors
- hf://PetrosStav/F5-TTS-Greek/vocab.txt

### Arguments

- Learning Rate: 0.00001
- Batch Size per GPU: 3200
- Max Samples: 64
- Gradient Accumulation Steps: 1
- Max Gradient Norm: 1
- Epochs: 277
- Warmup Updates: 1274
- Save per Updates: 25000
- Last per Steps: 1000
- mixed_precision: fp16


## Links:

- Github: https://github.com/SWivid/F5-TTS
- Paper: F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching (https://arxiv.org/abs/2410.06885)