| import gradio as gr |
| from transformers import VitsModel, AutoTokenizer |
| import torch |
|
|
| |
| print("Loading model...") |
| model = VitsModel.from_pretrained("facebook/mms-tts-kin") |
| tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-kin") |
| print("Model loaded successfully!") |
|
|
| def text_to_speech(text): |
| """ |
| Generate speech from Kinyarwanda text |
| |
| Args: |
| text: Input text in Kinyarwanda |
| |
| Returns: |
| Tuple of (sample_rate, audio_array) |
| """ |
| if not text or text.strip() == "": |
| return None |
| |
| try: |
| |
| inputs = tokenizer(text, return_tensors="pt") |
| |
| |
| with torch.no_grad(): |
| output = model(**inputs).waveform |
| |
| |
| audio_data = output.squeeze().cpu().numpy() |
| |
| |
| return (model.config.sampling_rate, audio_data) |
| |
| except Exception as e: |
| print(f"Error: {e}") |
| return None |
|
|
| |
| demo = gr.Interface( |
| fn=text_to_speech, |
| inputs=gr.Textbox( |
| label="Kinyarwanda Text", |
| placeholder="Enter text in Kinyarwanda (e.g., 'Muraho Rwanda')", |
| lines=3 |
| ), |
| outputs=gr.Audio(label="Generated Speech"), |
| title="🗣️ Kinyarwanda Text-to-Speech", |
| description=""" |
| Generate natural speech from Kinyarwanda text using Meta's MMS-TTS model. |
| |
| Simply enter text in Kinyarwanda and click Submit to hear it spoken. |
| |
| Model: [facebook/mms-tts-kin](https://huggingface.co/facebook/mms-tts-kin) |
| """, |
| examples=[ |
| ["Muraho"], |
| ["Mwaramutse"], |
| ["Amakuru"], |
| ["Murakoze cyane"], |
| ], |
| theme=gr.themes.Soft() |
| ) |
|
|
| |
| if __name__ == "__main__": |
| demo.launch(share=True) |
