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from transformers import pipeline | |
import gradio as gr | |
from pytube import YouTube | |
import os | |
pipe = pipeline(model="afroanton/whisper-small-sv-SE") # change to "your-username/the-name-you-picked" | |
def transcribe(audio): | |
text = pipe(audio)["text"] | |
return text | |
def transcribeUrl(url): | |
yt = YouTube(str(url)) | |
audio = yt.streams.filter(only_audio=True).first().download('yt_video') | |
text = pipe(audio)["text"] | |
return text | |
url_examples = [ | |
"https://www.youtube.com/watch?v=UuDQBjPDbbA&ab_channel=Nyhetsmorgon" | |
] | |
url_demo = gr.Interface( | |
fn=transcribeUrl, | |
examples=url_examples, | |
inputs="text", | |
outputs="text", | |
title="Whisper Small Swedish", | |
description="Swedish speech and audio recognition using a fine-tuned Whipser small model", | |
) | |
voice_demo = gr.Interface( | |
fn=transcribe, | |
inputs=gr.Audio(source="microphone", type="filepath"), | |
outputs="text", | |
title="Whisper Small Swedish", | |
description="Swedish speech and audio recognition using a fine-tuned Whipser small model", | |
) | |
demo = gr.TabbedInterface([url_demo, voice_demo], ["video-to-text", "voice-to-text"]) | |
if __name__ == "__main__": | |
demo.launch() | |