MMS English Female
This model is trained using IndicTTS dataset with Hindi female speaker.
Model
mms-english-female-indic: English model with Hindi female speaker from the IndicTTS dataset.
Sample Examples
| Text | Synthesized Audio |
|---|---|
| They decided to take a short break from work and travel to the mountains. | |
| I think that movie had a very unexpected and thrilling ending. | |
| It's always a good idea to double-check your work before submitting it. |
Inference
To use these models for inference, you'll need to install the transformers and accelerate libraries.
First, install the necessary libraries:
pip install --upgrade transformers accelerate
Then, run inference with the following code-snippet:
from transformers import VitsModel, AutoTokenizer
import torch
from IPython.display import Audio
model_path = "onecxi/mms-english-female-indic" # This is the path to your fine-tuned model
model = VitsModel.from_pretrained(model_path)
tokenizer = AutoTokenizer.from_pretrained(model_path)
text = "This is an English model trained using a Hindi female speaker."
inputs = tokenizer(text, return_tensors="pt")
with torch.no_grad():
output = model(**inputs).waveform
Audio(output.numpy(), rate=model.config.sampling_rate)
Disclaimer
This Text-to-Speech (TTS) model is intended solely for research and educational use. Any use of the model must comply with all applicable laws, regulations, and ethical standards. The unauthorized use of this model for impersonating real individuals without their explicit consent is strictly prohibited. Additionally, the model must not be used to create or distribute deceptive, misleading, or fraudulent content, including but not limited to fake news or scams. Any use of the model for illegal, harmful, or malicious purposes is expressly forbidden.
By using this model, you acknowledge and agree to these terms. The creators and distributors of the model disclaim any liability for misuse and do not support or condone unethical or unlawful applications.