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from transformers import pipeline
import gradio as gr
from pytube import YouTube
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
with gr.Blocks() as demo:
with gr.Tab("Real-time Swedish to English Transcription and Translation"):
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",
)
with gr.Tab("Youtube Video Transcription and Translation"):
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",
)
demo.launch(debug=True) |