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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() | |
text = pipe(audio)["text"] | |
return text | |
video_demo = gr.Interface.load( | |
fn=transcribeUrl, | |
inputs=gr.Textbox( | |
label="insert URL", | |
lines=3, | |
value="The fast brown fox jumps over lazy dogs.", | |
), | |
outputs="text", | |
title="Whisper Small Swedish", | |
description="Realtime demo for Swedish speech recognition using a fine-tuned Whisper small model.", | |
) | |
voice_demo = gr.Interface( | |
fn=transcribe, | |
inputs=gr.Audio(source="microphone", type="filepath"), | |
outputs="text", | |
title="Whisper Small Swedish", | |
description="Realtime demo for Swedish speech recognition using a fine-tuned Whisper small model.", | |
) | |
demo = gr.TabbedInterface([voice_demo, video_demo], ["voice to text", "video to text"]) | |
demo.launch() |