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import gradio as gr |
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import numpy as np |
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import spaces |
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from kokoro import KPipeline |
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pipeline = KPipeline(lang_code="j") |
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VOICES = [ |
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"jf_alpha", |
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"jf_gongitsune", |
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"jf_nezumi", |
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"jf_tebukuro", |
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"jm_kumo", |
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] |
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@spaces.GPU(duration=20) |
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def run(text: str, voice: str, speed: float) -> tuple[tuple[int, np.ndarray], str]: |
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generator = pipeline( |
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text, |
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voice=voice, |
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speed=speed, |
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split_pattern=r"\n+", |
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) |
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_, ps, audio = next(generator) |
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return (24000, audio.numpy()), ps |
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with gr.Blocks(css_paths="style.css") as demo: |
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gr.Markdown("# Kokoro (ja)") |
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with gr.Row(): |
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with gr.Column(): |
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input_text = gr.Textbox(label="Input Text") |
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voice = gr.Dropdown(label="Voice", choices=VOICES, value=VOICES[0]) |
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speed = gr.Slider(label="Speed", minimum=0.5, maximum=2.0, step=0.1, value=1.0) |
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run_button = gr.Button() |
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with gr.Column(): |
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output_audio = gr.Audio(label="Output Audio", autoplay=True) |
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output_tokens = gr.Textbox(label="Output Tokens") |
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gr.Examples( |
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examples=[ |
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"どうもこんにちは。今日はいい天気ですね。", |
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"隣の竹垣に竹立てかけたのは隣の竹垣に竹立てかけたかったからと骨粗鬆症の東京特許許可局局長がマサチューセッツ州の美術室で魔術師が呪術師と手術中に供述。", |
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"李も桃も桃のうち", |
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"隣の客はよく柿食う客だ", |
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"裏庭には二羽、庭には二羽、鶏がいる。", |
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"貴社の記者が汽車で帰社した。橋の端にある箸。石でできた医師。お食事券にまつわる汚職事件。", |
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], |
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inputs=input_text, |
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) |
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run_button.click( |
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fn=run, |
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inputs=[input_text, voice, speed], |
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outputs=[output_audio, output_tokens], |
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) |
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if __name__ == "__main__": |
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demo.launch() |
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