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Update app.py
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app.py
CHANGED
@@ -8,6 +8,12 @@ from voicefixer import VoiceFixer
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voicefixer = VoiceFixer()
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import gradio as gr
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import openai
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mes1 = [
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{"role": "system", "content": "You are a TOEFL examiner. Help me improve my oral Englsih and give me feedback."}
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@@ -70,9 +76,14 @@ def transcribe(apikey, upload, audio, choice1):
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voicefixer.restore(input="output.wav", # input wav file path
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output="audio1.wav", # output wav file path
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cuda=True, # whether to use gpu acceleration
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mode =
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return [result.text, chat_response, "
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output_1 = gr.Textbox(label="Speech to Text")
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output_2 = gr.Textbox(label="ChatGPT Output")
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voicefixer = VoiceFixer()
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import gradio as gr
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import openai
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import torchaudio
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from speechbrain.pretrained import WaveformEnhancement
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enhance_model = WaveformEnhancement.from_hparams(
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source="speechbrain/mtl-mimic-voicebank",
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savedir="pretrained_models/mtl-mimic-voicebank",
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)
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mes1 = [
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{"role": "system", "content": "You are a TOEFL examiner. Help me improve my oral Englsih and give me feedback."}
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voicefixer.restore(input="output.wav", # input wav file path
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output="audio1.wav", # output wav file path
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cuda=True, # whether to use gpu acceleration
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mode = 2) # You can try out mode 0, 1, or 2 to find out the best result
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enhanced = enhance_model.enhance_file("audio1.wav")
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# Saving enhanced signal on disk
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torchaudio.save("enhanced.wav", enhanced.unsqueeze(0).cpu(), 16000)
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return [result.text, chat_response, "enhanced.wav"]
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output_1 = gr.Textbox(label="Speech to Text")
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output_2 = gr.Textbox(label="ChatGPT Output")
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