|
from transformers import pipeline |
|
import gradio as gr |
|
from pytube import YouTube |
|
import os |
|
|
|
pipe = pipeline(model="afroanton/whisper-small-sv-SE") |
|
|
|
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() |
|
|
