---
tags:
- text-to-speech
- tts
- pytorch
language:
- ar
license: mit
---

# Multi-Speaker TTS Model

Trained Text-to-Speech model with the following specs:

## Model Details
- **Speakers:** 1
- **Mel Channels:** 80
- **Sample Rate:** 22050
- **Vocab Size:** 50000

## Training Stats
- **Final Mel Loss:** 5.3586
- **Validation Mel Loss:** 5.4784
- **Training Epochs:** 105

## Mel Normalization
- **Mean:** -4.8906
- **Std:** 4.9261

## Usage

```python
import torch
from transformers import AutoTokenizer

# Load model
checkpoint = torch.load('checkpoint_best.pt')
model = MultiSpeakerTTS(checkpoint['config'])
model.load_state_dict(checkpoint['model_state_dict'])
model.eval()

# Generate
tokenizer = AutoTokenizer.from_pretrained("miscovery/tokenizer_v3")
text = "Your text here"
tokens = tokenizer.encode(text)
# ... inference code ...
```

## Speaker Mapping
{
  "mahmoud": 0
}