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import gradio as gr |
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import os, torch, io |
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os.system('python -m unidic download') |
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from melo.api import TTS |
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speed = 1.0 |
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import tempfile |
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import nltk |
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nltk.download('averaged_perceptron_tagger_eng') |
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device = 'cuda' if torch.cuda.is_available() else 'cpu' |
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models = { |
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'EN': TTS(language='EN', device=device), |
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'ES': TTS(language='ES', device=device), |
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'FR': TTS(language='FR', device=device), |
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'ZH': TTS(language='ZH', device=device), |
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'JP': TTS(language='JP', device=device), |
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'KR': TTS(language='KR', device=device), |
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} |
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speaker_ids = models['EN'].hps.data.spk2id |
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default_text_dict = { |
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'EN': 'The field of text-to-speech has seen rapid development recently.', |
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'ES': 'El campo de la conversión de texto a voz ha experimentado un rápido desarrollo recientemente.', |
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'FR': 'Le domaine de la synthèse vocale a connu un développement rapide récemment', |
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'ZH': 'text-to-speech 领域近年来发展迅速', |
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'JP': 'テキスト読み上げの分野は最近急速な発展を遂げています', |
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'KR': '최근 텍스트 음성 변환 분야가 급속도로 발전하고 있습니다.', |
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} |
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def synthesize(text, speaker, speed, language, progress=gr.Progress()): |
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bio = io.BytesIO() |
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models[language].tts_to_file(text, models[language].hps.data.spk2id[speaker], bio, speed=speed, pbar=progress.tqdm, format='wav') |
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return bio.getvalue() |
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def load_speakers(language, text): |
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if text in list(default_text_dict.values()): |
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newtext = default_text_dict[language] |
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else: |
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newtext = text |
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return gr.update(value=list(models[language].hps.data.spk2id.keys())[0], choices=list(models[language].hps.data.spk2id.keys())), newtext |
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with gr.Blocks() as demo: |
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gr.Markdown('# MeloTTS Demo\n\nAn unofficial demo for [MeloTTS](https://github.com/myshell-ai/MeloTTS). **Make sure to try out several speakers, for example EN-Default!**') |
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with gr.Group(): |
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speaker = gr.Dropdown(speaker_ids.keys(), interactive=True, value='EN-US', label='Speaker') |
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language = gr.Radio(['EN', 'ES', 'FR', 'ZH', 'JP', 'KR'], label='Language', value='EN') |
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speed = gr.Slider(label='Speed', minimum=0.1, maximum=10.0, value=1.0, interactive=True, step=0.1) |
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text = gr.Textbox(label="Text to speak", value=default_text_dict['EN']) |
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language.input(load_speakers, inputs=[language, text], outputs=[speaker, text]) |
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btn = gr.Button('Synthesize', variant='primary') |
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aud = gr.Audio(interactive=False) |
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btn.click(synthesize, inputs=[text, speaker, speed, language], outputs=[aud]) |
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gr.Markdown('Demo by [mrfakename](https://twitter.com/realmrfakename).') |
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demo.queue(api_open=True, default_concurrency_limit=10).launch(show_api=True) |
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