metadata
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
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]