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import gradio as gr | |
import whisper | |
def speech_to_text(tmp_filename, model_size): | |
model = whisper.load_model(model_size) | |
result = model.transcribe(tmp_filename) | |
return result["text"] | |
gr.Interface( | |
title="Whisper by OpenAI", | |
description="Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web.", | |
fn=speech_to_text, | |
inputs=[ | |
gr.Audio(interactive=True,label="Record your voice on your mic",source="microphone", type="filepath"), | |
gr.Dropdown(label="Select model size",value="base",choices=["tiny", "base", "small", "medium", "large"])], | |
outputs="text").launch() | |