| import gradio as gr | |
| import os, torch, io | |
| os.system('python -m unidic download') | |
| from melo.api import TTS | |
| speed = 1.0 | |
| import tempfile | |
| device = 'cuda' if torch.cuda.is_available() else 'cpu' | |
| model = TTS(language='EN', device=device) | |
| speaker_ids = model.hps.data.spk2id | |
| def synthesize(speaker, text, speed=1.0, progress=gr.Progress()): | |
| with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as f: | |
| model.tts_to_file(text, speaker_ids[speaker], f.name, speed=speed, pbar=progress.tqdm) | |
| return f.name | |
| with gr.Blocks() as demo: | |
| gr.Markdown('# MeloTTS\n\nAn unofficial demo of [MeloTTS](https://github.com/myshell-ai/MeloTTS) from MyShell AI. MeloTTS is a permissively licensed (MIT) SOTA multi-speaker TTS model.\n\nI am not affiliated with MyShell AI in any way.\n\nThis demo currently only supports English, but the model itself supports other languages.') | |
| with gr.Group(): | |
| speaker = gr.Dropdown(speaker_ids.keys(), interactive=True, value='EN-Default', label='Speaker') | |
| speed = gr.Slider(label='Speed', minimum=0.1, maximum=10.0, value=1.0, interactive=True, step=0.1) | |
| text = gr.Textbox(label="Text to speak", value='The field of text to speech has seen rapid development recently') | |
| btn = gr.Button('Synthesize', variant='primary') | |
| aud = gr.Audio(interactive=False) | |
| btn.click(synthesize, inputs=[speaker, text, speed], outputs=[aud]) | |
| demo.queue(api_open=False, default_concurrency_limit=10).launch(show_api=False) | |