def extract_embedding(audio_path):
    signal = MODEL.load_audio(audio_path)
    if isinstance(signal, tuple):
        signal = signal[0]
    signal = signal.unsqueeze(0).to(DEVICE)
    with torch.no_grad():
        emb = MODEL.encode_batch(signal)
    return emb.squeeze().cpu().numpy().tolist()

def verify_speakers(audio_path, ref_path):
    score, pred = MODEL.verify_files(audio_path, ref_path)
    return float(score), bool(pred)