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import gradio as gr |
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import subprocess, os |
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import scripts.runSQ |
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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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print('about to setup') |
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setup() |
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def f1(voices, sent, indices): |
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tts_audio, tts_score, graph = scripts.runSQ.run(sent, [voices], indices) |
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score_report = f'Difference from TTS to real speech: {round(tts_score,2)}' |
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return (tts_audio, score_report, graph) |
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def label_indices(sentence): |
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sentence = scripts.runSQ.snorm(sentence) |
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sentence = sentence.split(' ') |
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labelled = [(f'{word} {i+1} ', str(i+1)) for i, word in enumerate(sentence)] |
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return labelled |
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bl = gr.Blocks() |
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with bl: |
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temp_sentences = ['Litlaus græn hugmynd?','Var það ekki nóg?', 'Ef svo er hvað heita þau þá?','Eru maríuhænur á Íslandi?'] |
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voices = ['Alfur','Dilja'] |
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temp_sentmenu = gr.Dropdown(temp_sentences, label="Sentence") |
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marked_sentence = gr.HighlightedText(interactive=False,label="Word selection key",color_map = {str(i):"#dcfce7" for i in range(333)}) |
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with gr.Row(): |
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spanselect = gr.Textbox(value='1-3',label="Select words",info='Enter the index of the word(s) to analyse, according to the key above. It can be a single word: 4 or a span of words separated by a dash: 2-3') |
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voiceselect = gr.Radio(voices, label="TTS voice",value='Alfur') |
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temp_button = gr.Button(value="Run with selected options") |
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tts_output = gr.Audio(interactive=False) |
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report_score = gr.Markdown('Difference from TTS to real speech:') |
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pl1 = gr.Plot() |
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temp_sentmenu.input(label_indices,temp_sentmenu,marked_sentence) |
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temp_button.click(f1,[voiceselect,temp_sentmenu,spanselect],[tts_output,report_score,pl1]) |
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if __name__ == "__main__": |
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bl.launch() |
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