File size: 1,443 Bytes
4300fed 205284d 406e977 4300fed b8401e1 4300fed 7a62809 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 |
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()):
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:
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)
|