import gradio as gr import os, torch, io import sys #os.system('python -m unidic download') from melo.api import TTS speed = 1.0 import tempfile if torch.cuda.is_available(): device = "cuda" elif torch.backends.mps.is_available(): device = "mps" else: device = "cpu" languages = ["EN", "ES", "FR", "ZH", "JP", "KR"] en = ["EN-Default", "EN-US", "EN-BR", "EN_INDIA", "EN-AU"] LANG = sys.argv[1] def synthesize(speaker, text, speed=1.0, progress=gr.Progress()): model = TTS(language=LANG, device=device) speaker_ids = model.hps.data.spk2id bio = io.BytesIO() model.tts_to_file(text, speaker_ids[speaker], bio, speed=speed, pbar=progress.tqdm, format='wav') return bio.getvalue() with gr.Blocks() as demo: with gr.Group(): if LANG == "EN": speaker = gr.Dropdown(en, interactive=True, value='EN-Default', label='Speaker') else: speaker = gr.Dropdown([LANG], interactive=True, value=LANG, 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)