The recent advancements in automatic speech recognition (ASR) systems have expedited their commercial deployment. Still, a major challenge faced by the current ASR systems is their poor performance for any mismatch between training and testing conditions. This book presents an in-depth analysis of multi- stream combination approach to improve the robustness of ASR systems for mismatch caused by additive noise. The book also discusses that multi-stream approach is complementary to other approaches for noise robustness, and how they can be used together. The selection of feature streams and allocation of weights to each feature stream are two important issues in multi-stream. Both the issues are analyzed, and a step-wise approach is presented to realize a significant improvement in performance by a multi-stream system compared to that of a state-of-the-art system. The analysis proposed in this work can also be applied to other pattern recognition tasks such as speaker recogntion and text-processing, rendering this book useful for a wide audience ranging from beginner to advance stage users working in ASR as well as other pattern recognition domains.