msmaje/voice_recognition

Voice Recognition Security Model

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

Usage

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]