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import gradio as gr | |
from transformers import pipeline | |
model = pipeline(task="automatic-speech-recognition", | |
model="facebook/s2t-medium-librispeech-asr") | |
def predict_speech_to_text(audio): | |
prediction = model(audio) | |
text = prediction['text'] | |
return text | |
gr.Interface(fn=predict_speech_to_text, | |
title="Automatic Speech Recognition (ASR)", | |
inputs=gr.inputs.Audio( | |
source="microphone", type="filepath", label="Input"), | |
outputs=gr.outputs.Textbox(label="Output"), | |
description="Using pipeline with Facebook S2T for ASR.", | |
examples=['ljspeech.wav'], | |
allow_flagging='never' | |
).launch() | |