Degrading the quality and intelligibility of the speech signals, background noise is a severe problem in communication and other speech related systems. The problem of speech signal filtration is dilated using computational algorithms and machines that offend the noise aspects of signal by through knowledge of source and channel. The speech filtration is key aspect for both: human ears and speech recognition applications. Noise Cancellation in Industrial Environment explain effects of industrial noise on speech signal and explores a range of algorithms for reducing their influence and improve the intelligibly and quality of speech signal. This book aims to make the available technology better known and explore new framework that can realistically achieved. For this purpose, this book presents speech and denoising models based on Independent Component Analysis (ICA), Particle Swarm Optimization (PSO) based thresholding strategies in discrete wavelet transform and Empirical Mode Decomposition (EMD).