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---
language: sw
license: cc-by-sa-4.0
tags:
- audio
- text-to-speech
inference: false
datasets:
- bookbot/OpenBible_Swahili
---
# VITS Base sw-KE-OpenBible
VITS Base sw-KE-OpenBible is an end-to-end text-to-speech model based on the [VITS](https://arxiv.org/abs/2106.06103) architecture. This model was trained from scratch on a real audio dataset. The list of real speakers include:
- sw-KE-OpenBible
The model's [vocabulary](https://huggingface.co/bookbot/vits-base-sw-KE-OpenBible/blob/main/symbols.py) contains the different IPA phonemes found in [gruut](https://github.com/rhasspy/gruut).
This model was trained using [VITS](https://github.com/jaywalnut310/vits) framework. All training was done on a Scaleway L40S VM with a NVIDIA L40S GPU. All necessary scripts used for training could be found in the [Files and versions](https://huggingface.co/bookbot/vits-base-sw-KE-OpenBible/tree/main) tab, as well as the [Training metrics](https://huggingface.co/bookbot/vits-base-sw-KE-OpenBible/tensorboard) logged via Tensorboard.
## Model
| Model | SR (Hz) | Mel range (Hz) | FFT / Hop / Win | #epochs |
| ------------------------- | ------- | -------------- | ----------------- | ------- |
| VITS Base sw-KE-OpenBible | 44.1K | 0-null | 2048 / 512 / 2048 | 12000 |
## Training procedure
### Prepare Data
```sh
python preprocess.py \
--text_index 1 \
--filelists filelists/sw-KE-OpenBible_text_train_filelist.txt filelists/sw-KE-OpenBible_text_val_filelist.txt \
--text_cleaners swahili_cleaners
```
### Train
```sh
python train.py -c configs/sw_ke_openbible_base.json -m sw_ke_openbible_base
```
## Frameworks
- PyTorch 2.2.2
- [VITS](https://github.com/bookbot-hive/vits) |