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from transformers import pipeline
import gradio as gr
from pytube import YouTube
import os
pipe = pipeline(model="CsanadT/whisper_small_sv")
def transcribe_live(audio):
text = pipe(audio)["text"]
return text
def transcribe_url(url):
youtube = YouTube(str(url))
audio = youtube.streams.filter(only_audio=True).first().download('yt_video')
text = pipe(audio)["text"]
return text
def transcribe_file(audio):
rate, y = audio
text = pipe(y)["text"]
return text
url_demo = gr.Interface(
fn = transcribe_url,
inputs = "text",
outputs = "text",
title = "Swedish Whisper",
description = "Fine-tuned Whisper model for swedish audio transcription",
)
voice_demo = gr.Interface(
fn=transcribe_live,
inputs=gr.Audio(source="microphone", type="filepath"),
outputs="text",
title="Whisper Swedish",
description="Fine-tuned Whisper model for swedish audio transcription",
)
file_demo = gr.Interface(
fn = transcribe_file,
inputs=gr.Audio(file_count="single"),
outputs="text",
title="Swedish Whisper",
description="Fine-tuned Whisper model for swedish audio transcription",
)
demo = gr.TabbedInterface([url_demo, voice_demo, file_demo], ["YouTube video transciption", "Live audio to Text", "Transcribe a file"])
demo.launch() |