Spaces:
Running
Running
| # !pip install TTS gradio numpy librosa torch | |
| from TTS.api import TTS | |
| import gradio as gr | |
| import numpy as np | |
| import librosa | |
| import torch | |
| import tempfile | |
| import os | |
| # Check device availability | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| # Initialize TTS model | |
| model_name = "tts_models/multilingual/multi-dataset/your_tts" | |
| tts = TTS(model_name=model_name).to(device) | |
| def process_audio(audio_path, max_duration=10): | |
| """Load and trim audio to specified duration""" | |
| y, sr = librosa.load(audio_path, sr=16000, mono=True) | |
| max_samples = max_duration * sr | |
| if len(y) > max_samples: | |
| y = y[:int(max_samples)] | |
| return y, sr | |
| def generate_speech(audio_file, text): | |
| # Create temp files | |
| with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as ref_file, \ | |
| tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as out_file: | |
| ref_path = ref_file.name | |
| out_path = out_file.name | |
| # Process reference audio | |
| y, sr = process_audio(audio_file) | |
| librosa.output.write_wav(ref_path, y, sr) | |
| # Generate speech | |
| try: | |
| tts.tts_to_file( | |
| text=text, | |
| speaker_wav=ref_path, | |
| language="en", | |
| file_path=out_path | |
| ) | |
| # Clean up temporary files | |
| os.unlink(ref_path) | |
| return out_path | |
| except Exception as e: | |
| print(f"Error: {e}") | |
| return None | |
| # Gradio interface | |
| with gr.Blocks(title="Voice Clone TTS") as demo: | |
| gr.Markdown(""" | |
| # 🎤 Voice Clone Text-to-Speech | |
| 1. Upload a short English voice sample (5-10 seconds) | |
| 2. Enter text you want to speak | |
| 3. Generate audio in your voice! | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| audio_input = gr.Audio( | |
| sources=["upload", "microphone"], | |
| type="filepath", | |
| label="Upload Voice Sample", | |
| interactive=True | |
| ) | |
| text_input = gr.Textbox( | |
| label="Text to Speak", | |
| placeholder="Enter English text here...", | |
| lines=4 | |
| ) | |
| btn = gr.Button("Generate Speech", variant="primary") | |
| with gr.Column(): | |
| audio_output = gr.Audio( | |
| label="Generated Speech", | |
| interactive=False | |
| ) | |
| error_output = gr.Textbox(label="Processing Info", visible=False) | |
| # Example inputs | |
| gr.Examples( | |
| examples=[ | |
| ["examples/sample_voice.wav", "Hello! Welcome to the future of voice cloning technology"], | |
| ["examples/sample_voice2.wav", "This text is spoken in a completely cloned voice"] | |
| ], | |
| inputs=[audio_input, text_input], | |
| outputs=audio_output, | |
| fn=generate_speech, | |
| cache_examples=True | |
| ) | |
| btn.click( | |
| fn=generate_speech, | |
| inputs=[audio_input, text_input], | |
| outputs=audio_output | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch(server_port=7860, share=True) |