asr / app.py
dawood's picture
dawood HF staff
Update app.py
d1f1348
raw
history blame
613 Bytes
from transformers import pipeline
import gradio as gr
model = pipeline("automatic-speech-recognition")
def transcribe_audio(mic=None, file=None):
if mic is not None:
audio = mic
elif file is not None:
audio = file
else:
return("You must either provide a mic recording or a file")
transcription = model(audio)["text"]
return transcription
gr.Interface(
fn=transcribe_audio,
inputs=[gr.Audio(source="microphone", type="filepath", optional=True),
gr.Audio(source ="upload", type="filepath", optional=True)],
outputs="text",
css=".footer{display:none !important}"
).launch()