| import gradio as gr | |
| from TTS.api import TTS | |
| tts = TTS("tts_models/multilingual/multi-dataset/xtts_v1") | |
| tts.to("cuda") | |
| def predict(prompt, language, audio_file_pth): | |
| tts.tts_to_file( | |
| text=prompt, | |
| file_path="output.wav", | |
| speaker_wav=audio_file_pth, | |
| language=language, | |
| ) | |
| return gr.make_waveform( | |
| audio="output.wav", | |
| ) | |
| title = "Coqui🐸 XTTS" | |
| description = """ | |
| <p>For faster inference without waiting in the queue, you should duplicate this space and upgrade to GPU via the settings. | |
| <br/> | |
| <a href="https://huggingface.co/spaces/coqui/xtts?duplicate=true"> | |
| <img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> | |
| </p> | |
| XTTS is a Voice generation model that lets you clone voices into different languages by using just a quick 3-second audio clip. | |
| Built on Tortoise, XTTS has important model changes that make cross-language voice cloning and multi-lingual speech generation super easy. | |
| <br/> | |
| This is the same model that powers Coqui Studio, and Coqui API, however we apply a few tricks to make it faster and support streaming inference. | |
| """ | |
| gr.Interface( | |
| fn=predict, | |
| inputs=[ | |
| gr.Textbox( | |
| label="Text Prompt", | |
| info="One or two sentences at a time is better", | |
| placeholder="It took me quite a long time to develop a voice, and now that I have it I'm not going to be silent.", | |
| ), | |
| gr.Dropdown( | |
| label="Language", | |
| info="Select an output language for the synthesised speech", | |
| choices=[ | |
| "en", | |
| "es", | |
| "fr", | |
| "de", | |
| "it", | |
| "pt", | |
| "pl", | |
| "tr", | |
| "ru", | |
| "nl", | |
| "cz", | |
| "ar", | |
| "zh", | |
| ], | |
| max_choices=1, | |
| value="en" | |
| ), | |
| gr.Audio( | |
| label="Reference Audio", | |
| info="Upload a reference audio for target speaker voice", | |
| type="filepath", | |
| value="examples/en_speaker_6.wav" | |
| ), | |
| ], | |
| outputs=[ | |
| gr.Video(label="Synthesised Speech"), | |
| ], | |
| title=title, | |
| ).launch(debug=True) | |