metadata
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
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 }