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| import gradio as gr | |
| def to_audioClassification(): | |
| return { | |
| audio_classification: gr.Row(visible=True), | |
| realtime_classification: gr.Row(visible=False), | |
| speech_recognition: gr.Row(visible=False), | |
| chatbot_qa: gr.Row(visible=False), | |
| } | |
| def to_realtimeAudioClassification(): | |
| return { | |
| audio_classification: gr.Row(visible=False), | |
| realtime_classification: gr.Row(visible=True), | |
| speech_recognition: gr.Row(visible=False), | |
| chatbot_qa: gr.Row(visible=False), | |
| } | |
| def to_speechRecognition(): | |
| return { | |
| audio_classification: gr.Row(visible=False), | |
| realtime_classification: gr.Row(visible=False), | |
| speech_recognition: gr.Row(visible=True), | |
| chatbot_qa: gr.Row(visible=False), | |
| } | |
| def to_chatbot(): | |
| return { | |
| audio_classification: gr.Row(visible=False), | |
| realtime_classification: gr.Row(visible=False), | |
| speech_recognition: gr.Row(visible=False), | |
| chatbot_qa: gr.Row(visible=True), | |
| } | |
| with gr.Blocks() as demo: | |
| with gr.Accordion("Settings", open=True): | |
| language = gr.Radio(["en-us", "pt-br"], label="Language", info="Choose the language to display the classification result and audio", value='en-us', interactive=True) | |
| with gr.Row(): | |
| btn0 = gr.Button("Audio Classification", scale=1, size='lg') | |
| btn1 = gr.Button("Realtime Audio Classification", scale=1,size='lg') | |
| btn2 = gr.Button("Speech Recognition", scale=1, size='lg') | |
| btn3 = gr.Button("Help", scale=1, size='lg') | |
| with gr.Row(visible=False) as audio_classification: | |
| with gr.Column(min_width=700): | |
| with gr.Accordion("Record an Audio", open=True): | |
| inputRecord = gr.Audio(label="Audio Input", source="microphone", type="filepath") | |
| with gr.Accordion("Upload a file", open=False): | |
| inputUpload = gr.Audio(label="Audio Input", source="upload", type="filepath") | |
| clearBtn = gr.ClearButton([inputRecord, inputUpload]) | |
| with gr.Column(min_width=700): | |
| output = gr.Label(label="Audio Classification") | |
| btn = gr.Button(value="Generate Audio") | |
| audioOutput = gr.Audio(label="Audio Output", interactive=False) | |
| with gr.Row(visible=False) as realtime_classification: | |
| with gr.Column(min_width=700): | |
| input = gr.Audio(label="Audio Input", source="microphone", type="filepath",streaming=True, every=10) | |
| historyOutput = gr.Textbox(label="History", interactive=False) | |
| # historyOutput = gr.Label(label="History") | |
| with gr.Column(min_width=700): | |
| output = gr.Label(label="Audio Classification") | |
| with gr.Row(visible=False) as speech_recognition: | |
| with gr.Column(min_width=700): | |
| with gr.Accordion("Record an Audio", open=True): | |
| inputRecord = gr.Audio(label="Audio Input", source="microphone", type="filepath") | |
| with gr.Accordion("Upload a file", open=False): | |
| inputUpload = gr.Audio(label="Audio Input", source="upload", type="filepath") | |
| clearBtn = gr.ClearButton([inputRecord]) | |
| with gr.Column(min_width=700): | |
| output = gr.Label(label="Transcription") | |
| with gr.Row(visible=False) as chatbot_qa: | |
| chatbot = gr.Chatbot( | |
| [], | |
| elem_id="chatbot", | |
| bubble_full_width=False, | |
| # avatar_images=(None, "/content/avatar-socialear.png"), | |
| min_width=2000 | |
| ) | |
| with gr.Row(min_width=2000): | |
| txt = gr.Textbox( | |
| scale=4, | |
| show_label=False, | |
| placeholder="Enter text and press enter", | |
| container=False, | |
| min_width=1000 | |
| ) | |
| submit = gr.Button(value="", size='sm', scale=1) | |
| btn0.click(fn=to_audioClassification, outputs=[audio_classification, realtime_classification, speech_recognition, chatbot_qa]) | |
| btn1.click(fn=to_realtimeAudioClassification, outputs=[audio_classification, realtime_classification, speech_recognition, chatbot_qa]) | |
| btn2.click(fn=to_speechRecognition, outputs=[audio_classification, realtime_classification, speech_recognition, chatbot_qa]) | |
| btn3.click(fn=to_chatbot, outputs=[audio_classification, realtime_classification, speech_recognition, chatbot_qa]) | |
| if __name__ == "__main__": | |
| demo.queue() | |
| demo.launch() |