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import gradio as gr
from pydub import AudioSegment
from faster_whisper import WhisperModel
import os
model = WhisperModel("openai/whisper-large-v3-turbo", compute_type="int8")
def convert_to_wav(file_path):
audio = AudioSegment.from_file(file_path)
audio = audio.set_frame_rate(16000).set_channels(1).set_sample_width(2)
out_path = file_path.replace(".", "_ready.")
audio.export(out_path, format="wav")
return out_path
def detect_language(audio_file):
wav = convert_to_wav(audio_file.name)
segments, info = model.transcribe(wav)
transcript = "\n".join([seg.text for seg in segments])
return f"🌐 Language: {info.language}\n\n📝 Transcript:\n{transcript}"
gr.Interface(fn=detect_language,
inputs=gr.Audio(type="filepath"),
outputs="text",
title="🎧 Audio Language Detector",
description="Drop any MP3/WAV/FLAC to identify spoken language & get transcript."
).launch()
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