---
language: en
tags:
- audio
- voice-recognition
- security
- pytorch
license: apache-2.0
datasets:
- your-dataset-name
---

# Voice Recognition Security Model

This model provides secure voice recognition with transfer learning and data augmentation.

## Usage

```python
from transformers import AutoModel
import torch
import joblib
import librosa
import numpy as np

# Load model
model = AutoModel.from_pretrained("your-username/your-model-name")
label_encoder = joblib.load("label_encoder.joblib")
feature_params = joblib.load("feature_params.joblib")

# Prediction function
def predict_voice(file_path):
    # Extract features (same as during training)
    features = extract_features(file_path, feature_params['max_pad_len'])
    features = torch.tensor(features).unsqueeze(0).unsqueeze(0)
    
    # Predict
    with torch.no_grad():
        outputs = model(features)
        _, predicted = torch.max(outputs, 1)
    
    return label_encoder.inverse_transform([predicted.item()])[0]