Upload app.py
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app.py
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import gradio as gr
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import httpx
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async def call_api(text: str, audio_path: str):
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# 读取音频文件
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return response.json()["result"]
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def load_examples():
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return [
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["Can you turn my English into German?", "./show_case/common_voice_en_19664034.mp3"], # En-De
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["Can you identify the initial word that connects to 'currency_name' in this audio clip?",
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"./show_case/audio-1434542201-headset.wav"], # ER
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["What do you think the speaker's message is intended to be in this audio?",
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"./show_case/audio-1434542201-headset.wav"], # IC
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["What does the person say?", "./show_case/p225_002.wav"], # DFake
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["Assess whether this speech's pronunciation is Real or Fake.", "./show_case/Fake.wav"], # DFake
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[
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"What emotional weight does the speaker's tone carry?\nPick one answer from A, B, C, and D.\nA: fear\nB: sadness\nC: joy\nD: neutral",
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"./show_case/SER(emotion)_example.wav"], # SER(emotion)
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[
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"Choose the most suitable answer from options A, B, C, and D to respond the question in next line, you may only choose A or B or C or D.\nThe number of speakers delivering this speech is what?\nA. 4\nB. 2\nC.1\nD. 3",
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"./show_case/SNV_example.wav"], # SNV
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["Identify the language of the conversation you just heard.", "./show_case/SLR_example.wav"], # SLR
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["tell the gender of the speaker in this audio.", "./show_case/SGR_018.wav"], # SGR
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["What's the sound we're hearing in this audio from?", "./show_case/Sound_Vocal_example.wav"], # Sound_vocal
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["What is your best guess at the setting of this sound clip?", "./show_case/Scene_example.wav"], # Sound_cochl
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[
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"Choose the most suitable answer from options A, B, C, and D to respond the question in next line, Please think step by step and you may only choose A or B or C or D.\nRecognize the segment where 'project' is spoken by the speaker.\nA. [5.28, 5.39]\nB. [0.92, 1.39]\nC. [4.75, 5.28]\nD. [3.86, 4.23]",
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"./show_case/SG_audio_1.wav"], # SG
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["What type of business does the first person's son have?", "./show_case/SFT_Fisher_example.wav"] # SFT_Fisher
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]
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iface = gr.Interface(
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fn=call_api,
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inputs=[
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gr.Audio(type="filepath", label="Upload Audio", value="./show_case/p225_002.wav")
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],
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outputs=gr.Textbox(label="Model output"),
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examples=
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allow_flagging="never"
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)
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# Add a button to load examples
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iface.add_button("Show Example", load_examples)
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iface.launch()
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if __name__ == '__main__':
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pass
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# frontend.py
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import gradio as gr
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import httpx
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examples = [
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["Can you turn my English into German?", "./show_case/common_voice_en_19664034.mp3"], # En-De
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["Can you identify the initial word that connects to 'currency_name' in this audio clip?", "./show_case/audio-1434542201-headset.wav"], # ER
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["What do you think the speaker's message is intended to be in this audio?", "./show_case/audio-1434542201-headset.wav"], # IC
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["What does the person say?", "./show_case/p225_002.wav"], # DFake
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# ["Assess whether this speech's pronunciation is Real or Fake.", "./show_case/Real.wav"], # DFake
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["Assess whether this speech's pronunciation is Real or Fake.", "./show_case/Fake.wav"], # DFake
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["What emotional weight does the speaker's tone carry?\nPick one answer from A, B, C, and D.\nA: fear\nB: sadness\nC: joy\nD: neutral", "./show_case/SER(emotion)_example.wav"], #SER(emotion)
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# ["Assess whether this speech's pronunciation is Real or Fake.", "./show_case/SVD_14154_file31512.mp3.wav_16k.wav_norm.wav_mono.wav_silence.wav"], # SVD
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["Choose the most suitable answer from options A, B, C, and D to respond the question in next line, you may only choose A or B or C or D.\nThe number of speakers delivering this speech is what?\nA. 4\nB. 2\nC.1\nD. 3", "./show_case/SNV_example.wav"], #SNV
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["Identify the language of the conversation you just heard.","./show_case/SLR_example.wav"], #SLR
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["tell the gender of the speaker in this audio.","./show_case/SGR_018.wav"], #SGR
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["What's the sound we're hearing in this audio from?","./show_case/Sound_Vocal_example.wav"], #Sound_vocal
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["What is your best guess at the setting of this sound clip?","./show_case/Scene_example.wav"], #Sound_cochl
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["Choose the most suitable answer from options A, B, C, and D to respond the question in next line, Please think step by step and you may only choose A or B or C or D.\nRecognize the segment where 'project' is spoken by the speaker.\nA. [5.28, 5.39]\nB. [0.92, 1.39]\nC. [4.75, 5.28]\nD. [3.86, 4.23]","./show_case/SG_audio_1.wav"], #SG
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["What type of business does the first person's son have?","./show_case/SFT_Fisher_example.wav"] #SFT_Fisher
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]
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async def call_api(text: str, audio_path: str):
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# 读取音频文件
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return response.json()["result"]
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iface = gr.Interface(
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fn=call_api,
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inputs=[
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gr.Audio(type="filepath", label="Upload Audio", value="./show_case/p225_002.wav")
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],
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outputs=gr.Textbox(label="Model output"),
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examples=examples,
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allow_flagging="never"
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)
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iface.launch()
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if __name__ == '__main__':
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# curl -X POST -F "text=What does the person say?" -F "audio_file=@./test_audio.wav" http://36.151.70.8:30113/process/
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pass
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