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import os |
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os.system("pip install gradio==2.4.6") |
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import gradio as gr |
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title = "fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit" |
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description = "Gradio Demo for fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit. To use it, simply add your text, or click one of the examples to load them. Read more at the links below." |
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2109.06912' target='_blank'>fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit</a> | <a href='https://github.com/pytorch/fairseq/tree/main/examples/speech_synthesis' target='_blank'>Github Repo</a></p>" |
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examples = [ |
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["Hello this is a test run","fastspeech2-en-200_speaker-cv4"], |
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["Hello, this is a test run.","tts_transformer-en-200_speaker-cv4"], |
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["Bonjour, ceci est un test.","tts_transformer-fr-cv7_css10"], |
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["BЗдравствуйте, это пробный запуск.","tts_transformer-ru-cv7_css10"], |
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["Merhaba, bu bir deneme çalışmasıdır.","tts_transformer-tr-cv7"], |
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] |
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io1 = gr.Interface.load("huggingface/facebook/fastspeech2-en-200_speaker-cv4") |
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io2 = gr.Interface.load("huggingface/facebook/tts_transformer-en-200_speaker-cv4") |
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io3 = gr.Interface.load("huggingface/facebook/tts_transformer-fr-cv7_css10") |
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io4 = gr.Interface.load("huggingface/facebook/tts_transformer-ru-cv7_css10") |
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io5 = gr.Interface.load("huggingface/facebook/tts_transformer-tr-cv7") |
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def inference(text,model): |
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if model == "fastspeech2-en-200_speaker-cv4": |
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outtext = io1(text) |
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elif model == "tts_transformer-en-200_speaker-cv4": |
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outtext = io2(text) |
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elif model == "tts_transformer-fr-cv7_css10": |
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outtext = io3(text) |
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elif model == "tts_transformer-ru-cv7_css10": |
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outtext = io4(text) |
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else: |
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outtext = io5(text) |
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return outtext |
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gr.Interface( |
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inference, |
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[gr.inputs.Textbox(label="Input",lines=5),gr.inputs.Dropdown(choices=["fastspeech2-en-200_speaker-cv4","tts_transformer-en-200_speaker-cv4","tts_transformer-tr-cv7","tts_transformer-fr-cv7_css10","tts_transformer-ru-cv7_css10"], type="value", default="fastspeech2-en-200_speaker-cv4", label="model") |
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], |
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gr.outputs.Audio(label="Output"), |
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examples=examples, |
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article=article, |
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title=title, |
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description=description, |
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enable_queue=True).launch() |