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import whisper
import gradio as gr
model = whisper.load_hf_model(repo_id="jerpint/whisper", filename="base.pt")
def transcribe(audio, translate):
task = "translate" if translate else None
result = model.transcribe(audio, task=task)
return result["text"]
title = "BabelFish"
description = "Record your voice in any language, babelfish will output a transcript of what was said. Check 'Translate to english' to get an english transcription. Based on the OpenAI Whisper model"
gr.Interface(
fn=transcribe,
inputs=[
gr.Audio(source="microphone", type="filepath"),
gr.Checkbox(label="Translate to english"),
],
title=title,
description=description,
examples=[
["samples/french_hello.wav", True],
["samples/english_hello.wav", True],
["samples/hebrew_hello.wav", True],
["samples/spanish_hello.wav", True],
],
outputs="text",
).launch()
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