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import gradio as gr |
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import subprocess,os |
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from datasets import load_dataset, Audio |
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import matplotlib |
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matplotlib.use('Agg') |
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import matplotlib.pyplot as plt |
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def setup(): |
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r0 = subprocess.run(["pwd"], capture_output=True, text=True) |
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print('PWD::', r0.stdout) |
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r1 = subprocess.run(["wget", "https://github.com/google/REAPER/archive/refs/heads/master.zip"], capture_output=True, text=True) |
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print(r1.stdout) |
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subprocess.run(["unzip", "./master.zip"]) |
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subprocess.run(["mv", "REAPER-master", "REAPER"]) |
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subprocess.run(["rm", "./master.zip"]) |
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os.chdir('./REAPER') |
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subprocess.run(["mkdir", "build"]) |
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os.chdir('./build') |
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r2 = subprocess.run(["cmake", ".."], capture_output=True, text=True) |
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print(r2.stdout) |
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r3 = subprocess.run(["make"], capture_output=True, text=True) |
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print(r3.stdout) |
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os.chdir('../..') |
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r9 = subprocess.run(["ls", "-la"], capture_output=True, text=True) |
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print('LS::', r9.stdout) |
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def load_lang(langname): |
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if langname=="Icelandic": |
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dsname = "language-and-voice-lab/samromur_asr" |
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ds = load_dataset(dsname,split='validation') |
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ds = ds.cast_column("audio", Audio(sampling_rate=16_000)) |
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df = ds.data.to_pandas() |
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df = df.drop(columns=['audio', 'speaker_id','duration']) |
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return df |
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def f1(): |
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fig = plt.figure(figsize=(10,4)) |
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plt.axline((0,0),slope=1,color="darkgray") |
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plt.xlabel("Vowel length (ms)") |
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plt.ylabel("Consonant length (ms)") |
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return(fig) |
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bl = gr.Blocks() |
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with bl: |
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btn1 = gr.Button(value="The random prosody button") |
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btn1.style(full_width=False, size="sm") |
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pl1 = gr.Plot() |
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btn1.click(f1, [], pl1) |
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lloadr = gr.Dropdown(["Faroese", "Icelandic"], label="Language", info="Load data for selection...") |
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with gr.Row(): |
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databrowser = gr.DataFrame(wrap=True, max_rows=50, interactive=False, overflow_row_behaviour='paginate') |
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lloadr.change(load_lang,lloadr,databrowser) |
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if __name__ == "__main__": |
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bl.launch() |
