v1-vits-model

my_vits_model

Model Description

A VITS-based TTS model for English speech synthesis

• Language(s): English
• Type: Single-speaker Text-to-Speech
• Model Type: VITS
• Framework: Coqui TTS
• Uploaded: 2025-05-29

Intended Use

• Primary Use: Generating single-speaker speech from text input for applications like virtual assistants, audiobooks, or accessibility tools.
• Out of Scope: Real-time applications if not optimized for low latency.

Usage

To load and use the model:

from safetensors.torch import load_file
from TTS.config import load_config
from TTS.tts.models import setup_model

# Load configuration
config = load_config("config.json")
model = setup_model(config)

# Load weights
state_dict = load_file("my_vits_model.safetensors")
model.load_state_dict(state_dict)
model.eval()

# Example inference
text = "Hello, this is a test."
wav = model.inference(text, speaker_id=0 if False else None)

Training Data

• Dataset: Custom dataset
• Preprocessing: Text normalized, audio sampled at 22050 Hz

Evaluation

• Metrics: [Add metrics, e.g., Mean Opinion Score (MOS), Word Error Rate (WER)]
• Results: [Add results, e.g., "Achieved MOS of 4.2 on test set"]

Limitations

• Limited to English language(s).
• Performance may vary with noisy or complex input text.

License

• Released under apache-2.0.

Ethical Considerations

• Ensure responsible use to avoid generating misleading or harmful audio content.
• Verify input text to prevent biased or offensive outputs.

Dependencies

• TTS (Coqui TTS)
• safetensors
• torch