Speech Recognition Using Artificial Neural Networks

This speech recognition technology utilizes artificial neural networks (ANN) by integrating Linear Predictive Coding (LPC) parameters extracted from speech signals with neural network-based classification. The implementation involves using MATLAB for system development, debugging, and performance optimization. Key technical components include: - LPC parameter extraction: Using MATLAB's signal processing toolbox to compute linear prediction coefficients that represent vocal tract characteristics - Neural network architecture: Implementing feedforward or recurrent neural networks with appropriate activation functions and layer configurations - Training methodology: Employing backpropagation algorithms with gradient descent optimization for network weight adjustments - Performance optimization: Conducting systematic debugging and parameter tuning to enhance recognition accuracy and computational efficiency The system demonstrates improved capability in processing diverse speech inputs, achieving more accurate and reliable recognition results through the synergistic combination of signal processing techniques and machine learning approaches. The MATLAB implementation allows for efficient prototyping and validation of various network architectures and parameter configurations.