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import gradio as gr
import yt_dlp
from transformers import pipeline
from gtts import gTTS
# Load pipelines
asr = pipeline("automatic-speech-recognition", model="openai/whisper-base", task="transcribe")
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-hi")
def youtube_to_hindi_dub(url):
# Step 1: Download audio from YouTube
ydl_opts = {
'format': 'bestaudio/best',
'outtmpl': 'audio.%(ext)s',
'postprocessors': [{'key': 'FFmpegExtractAudio', 'preferredcodec': 'mp3'}],
'quiet': True
}
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
ydl.download([url])
audio_path = "audio.mp3"
# Step 2: Transcribe English
result = asr(audio_path)
english_text = result["text"]
# Step 3: Translate to Hindi
hindi_text = translator(english_text)[0]['translation_text']
# Step 4: Convert to Hindi Audio
tts = gTTS(hindi_text, lang="hi")
tts.save("dubbed.mp3")
return "dubbed.mp3"
# Gradio UI
iface = gr.Interface(
fn=youtube_to_hindi_dub,
inputs=gr.Textbox(label="YouTube Video Link"),
outputs=gr.Audio(label="Dubbed Hindi Audio", type="filepath"),
title="🎧 YouTube Video to Hindi Dubber",
description="Paste an English YouTube link, and get Hindi AI voice dubbing."
)
iface.launch() |