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from transformers import pipeline | |
import gradio as gr | |
transcription_pipe = pipeline(model="explorall/whisper-small-sv-dropout-6mb") | |
translation_pipe = pipeline(model="Helsinki-NLP/opus-mt-sv-en") | |
def transcribe_and_translate(audio): | |
transcription = transcription_pipe(audio)["text"] | |
translation = translation_pipe(transcription)[0]['translation_text'] | |
return transcription, translation | |
iface = gr.Interface( | |
fn=transcribe_and_translate, | |
inputs=gr.Audio(source="microphone", type="filepath"), | |
outputs=[gr.Textbox(), gr.Textbox()], | |
title="Whisper Small Swedish to English Translator", | |
description="Realtime demo for Swedish speech recognition using a fine-tuned Whisper small model, and Swedish to English translation using a small T5 model", | |
) | |
iface.launch() |