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| import os | |
| os.system("""pip install nemo_toolkit['all']""") | |
| import nemo.collections.asr as nemo_asr | |
| from transformers import pipeline | |
| import numpy as np | |
| import gradio as gr | |
| import librosa | |
| from scipy.io.wavfile import write | |
| def respond(message, chat_history): | |
| bot_message = message | |
| chat_history.append((message, bot_message)) | |
| return "", chat_history | |
| def transcribe(audio): | |
| sr, y = audio | |
| audio_name = "resampled_audio.wav" | |
| resampled_audio = librosa.resample(y=y.astype("float"), orig_sr=sr, target_sr=16000) | |
| write(audio_name, 16000, resampled_audio) | |
| result = asr_model.transcribe([f"./{audio_name}"]) | |
| return result[0] | |
| asr_model = nemo_asr.models.EncDecCTCModel.from_pretrained(model_name="nvidia/parakeet-ctc-0.6b") | |
| with gr.Blocks() as demo: | |
| with gr.Column(): | |
| gr.Markdown( | |
| """ | |
| # HKU Canteen VA | |
| """) | |
| va = gr.Chatbot(container=False) | |
| with gr.Row(): # text input | |
| text_input = gr.Textbox(placeholder="Ask me anything...", container=False, scale=1) | |
| submit_btn = gr.Button("Submit", scale=0) | |
| with gr.Row(): # audio input | |
| recording = gr.Microphone(show_download_button=False, container=False) | |
| with gr.Row(): # button toolbar | |
| clear = gr.ClearButton([text_input, va]) | |
| text_input.submit(respond, [text_input, va], [text_input, va], queue=False) | |
| submit_btn.click(respond, [text_input, va], [text_input, va], queue=False) | |
| # recording.stop_recording(transcribe, [recording], [text_input]).then(respond,s [text_input, va], [text_input, va], queue=False) | |
| recording.stop_recording(transcribe, [recording], [text_input]) | |
| if __name__ == "__main__": | |
| demo.launch() |