---
license: other
license_name: coqui-public-model-license
license_link: https://coqui.ai/cpml
library_name: coqui
pipeline_tag: text-to-speech
datasets:
- ylacombe/google-argentinian-spanish
language:
- es
---
# ⓍTTS 🇦🇷
ⓍTTS is a Voice generation model that lets you clone voices into different languages by using just a quick 6-second audio clip. There is no need for an excessive amount of training data that spans countless hours.

This model was trained by [CITECCA](https://mapatecnologico.rionegro.gov.ar/detail/citecca-centro-interdisciplinario-de-telecomunicaciones-electronica-computacion-y-ciencia-aplicada-unrn) in the [Universidad Nacional de Rio Negro](https://www.unrn.edu.ar/home)

### Language
This model's Spanish language has been finetuned using [ylacombe's google argentinian spanish dataset](https://huggingface.co/datasets/ylacombe/google-argentinian-spanish) to archieve an argentinian accent.

### Training Parameters

```
batch_size=8,
grad_accum_steps=96,
batch_group_size=48,
eval_batch_size=8,
num_loader_workers=8,
eval_split_max_size=256,
optimizer="AdamW",
optimizer_wd_only_on_weights=True,
optimizer_params={"betas": [0.9, 0.96], "eps": 1e-8, "weight_decay": 1e-2},
lr=5e-06, 
lr_scheduler="MultiStepLR",
lr_scheduler_params={"milestones": [50000 * 18, 150000 * 18, 300000 * 18], "gamma": 0.5, "last_epoch": -1},
```

### License
This model is licensed under [Coqui Public Model License](https://coqui.ai/cpml). There's a lot that goes into a license for generative models, and you can read more of [the origin story of CPML here](https://coqui.ai/blog/tts/cpml).

Using 🐸TTS Command line:

```console
 tts --model_name /path/to/xtts/ \
     --text "Che boludo, vamos a tomar unos mates." \
     --speaker_wav /path/to/target/speaker.wav \
     --language_idx es \
     --use_cuda true
```

Using the model directly:

```python
from TTS.tts.configs.xtts_config import XttsConfig
from TTS.tts.models.xtts import Xtts

config = XttsConfig()
config.load_json("/path/to/xtts/config.json")
model = Xtts.init_from_config(config)
model.load_checkpoint(config, checkpoint_dir="/path/to/xtts/", eval=True)
model.cuda()

outputs = model.synthesize(
    "Che boludo, vamos a tomar unos mates.",
    config,
    speaker_wav="/data/TTS-public/_refclips/3.wav",
    gpt_cond_len=3,
    language="es",
)
```