fala_pb_checkpoints / README.md
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---
language:
- pt
tags:
- text-to-speech
- tts
- voice-cloning
- portuguese
- pt-br
- fine-tuning
license: other
license_name: mixed
license_details: Each model inherits the license of its base model see the table below and each folder's README.
pipeline_tag: text-to-speech
base_model:
- firstpixel/F5-TTS-pt-br
- coqui/XTTS-v2
- Qwen/Qwen3-TTS-12Hz-1.7B-Base
- fishaudio/fish-speech-1.5
- canopylabs/3b-es_it-ft-research_release
base_model_relation: finetune
---
# Brazilian Portuguese TTS Checkpoints — Paraíba Accent
Fine-tuning checkpoints of five Text-to-Speech frameworks for **Brazilian Portuguese (Paraíba accent)**, produced for the master's dissertation *Incorporando Regionalismos e Sotaques em Modelos de Síntese de Fala* (Thomaz Diniz, UFCG, 2026). All experiments share the same voice corpus (FALA_PB) and include checkpoints, evaluation audio, loss curves, and training reports.
**Every checkpoint in this repository is a fine-tune of its respective base model** (listed below and in the References section) — except `F5TTS/filtered_zero_experiment/`, which was trained from scratch as a control experiment.
## Models
| Folder | Base / starting checkpoint | Method | Size | Base license |
|---|---|---|---|---|
| [`F5TTS/`](F5TTS/README.md) | F5-TTS pt-br by **firstpixel** | Full fine-tuning (+ one from-scratch run) | ~21 GB | CC-BY-NC-4.0 |
| [`XTTS/`](XTTS/README.md) | XTTS v2 (Coqui) | GPT fine-tuning | ~37 GB | Coqui Public Model License |
| [`QwenTTS/`](QwenTTS/README.md) | Qwen3-TTS-12Hz-1.7B-Base | Full fine-tuning | ~13 GB | Apache-2.0 |
| [`FishSpeech/`](FishSpeech/README.md) | Fish Speech 1.5 | LoRA + merge | ~2.5 GB | CC-BY-NC-SA-4.0 |
| [`OrpheusTTS/`](OrpheusTTS/README.md) | Orpheus 3B (es_it) + **ArtooDtoo** PT-BR adapter | LoRA (Unsloth) | ~800 MB | Llama 3 / Apache-2.0 |
## Repository layout
Every model folder (or training folder, for F5TTS) follows the same pattern:
```
<Model>/
├── checkpoints # .pt/.pth/.ckpt files or framework-format folders
├── configs & reports # setting.json, REPORT.md, etc.
├── graficos/ # loss curves and metrics (PNG + CSV)
└── inferencias/ # evaluation audio (.wav) + phrases/manifests
```
- `F5TTS/` has one extra level for its 3 training runs: `all/`, `filtered/`, `filtered_zero_experiment/`
- Folder-format checkpoints: `QwenTTS/checkpoint-step-*/`, `FishSpeech/final_merged_llama/`, `OrpheusTTS/final_adapter/`
## Training data
Proprietary Brazilian Portuguese voice corpus with Paraíba accent (~41k segments, ~4 s average per sample). The dataset itself is **not** included in this repository — only the checkpoints, metrics, and generated evaluation audio.
## Usage
Each model's README states the framework and version used for training. In short: load the checkpoint with the official inference pipeline of the corresponding framework (F5-TTS, Coqui TTS, Qwen3-TTS, Fish Speech, or Orpheus/Unsloth).
## References — base models and starting checkpoints
The experiments started from the following models/checkpoints:
- **F5-TTS**: fine-tuned from the Brazilian Portuguese checkpoint by firstpixel — [firstpixel/F5-TTS-pt-br](https://huggingface.co/firstpixel/F5-TTS-pt-br) (`firstpixelptbr/model_last.pt`), built on [F5-TTS](https://github.com/SWivid/F5-TTS) (SWivid). The `filtered_zero_experiment` run was trained from scratch (no pretrained weights).
- **XTTS v2**: fine-tuned from [coqui/XTTS-v2](https://huggingface.co/coqui/XTTS-v2) (Coqui AI).
- **Qwen3-TTS**: fine-tuned from [Qwen/Qwen3-TTS-12Hz-1.7B-Base](https://huggingface.co/Qwen) (Alibaba/Qwen).
- **Fish Speech**: LoRA fine-tuned from [fishaudio/fish-speech-1.5](https://huggingface.co/fishaudio/fish-speech-1.5) (Fish Audio).
- **Orpheus TTS**: LoRA fine-tuned with [Unsloth](https://github.com/unslothai/unsloth) from [canopylabs/3b-es_it-ft-research_release](https://huggingface.co/canopylabs/3b-es_it-ft-research_release) (Canopy Labs), continuing from the PT-BR adapter [ArtooDtoo/Orpheus_PTBR_FT_Unsloth_Chk-1800](https://huggingface.co/ArtooDtoo/Orpheus_PTBR_FT_Unsloth_Chk-1800).
## Citation
If you use these checkpoints, please cite the master's dissertation:
**ABNT:**
> DINIZ, Thomaz. **Incorporando regionalismos e sotaques em modelos de síntese de fala**. 2026. Dissertação (Mestrado em Ciência da Computação) — Universidade Federal de Campina Grande, Campina Grande, 2026.
**BibTeX:**
```bibtex
@mastersthesis{diniz2026regionalismos,
author = {Diniz, Thomaz},
title = {Incorporando Regionalismos e Sotaques em Modelos de S{\'i}ntese de Fala},
school = {Universidade Federal de Campina Grande},
address = {Campina Grande, Brazil},
year = {2026},
type = {Master's dissertation}
}
```