Deep Filtering: Signal Extraction and Reconstruction Using Deep Neural Networks

This paper introduces a deep learning approach for audio signal processing, specifically focusing on extracting desired signals and removing noise. It uses deep neural networks to learn complex relationships between noisy and clean audio, allowing for effective noise reduction and signal reconstruction. This technique is particularly useful for enhancing audio quality in various applications by filtering out unwanted background noise.