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import os
import gradio as gr
from transformers import pipeline
title = "Transcribe speech in German"
pipeline = pipeline(task="automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-german")
#pipeline = pipeline(task="automatic-speech-recognition", model="openai/whisper-large")
def transcribeFile(audio_path : str) -> str:
transcription = pipeline(audio_path)
return transcription["text"]
app1 = gr.Interface(
fn=transcribeFile,
inputs=gr.inputs.Audio(label="Upload audio file", type="filepath"),
outputs="text",
title=title
)
app2 = gr.Interface(
fn=transcribeFile,
inputs=gr.Audio(source="microphone", type="filepath"),
outputs="text",
title=title
)
demo = gr.TabbedInterface([app1, app2], ["Audio File", "Microphone"])
if __name__ == "__main__":
demo.launch()
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