Machine audition is the field of the study of algorithms and systems for the automatic analysis and understanding of sound by machine. It plays an important role in many applications, such as automatic audio indexing for internet searching, robust speech recognition in un-controlled natural environment, untethered audio communication within an intelligent office scenario, and speech enhancement for hearing aids and cochlear implants, etc. It has recently attracted increasing interest within several research communities, such as signal processing, machine learning, auditory modelling, perception and cognition, psychology, pattern recognition, and artificial intelligence. However, the developments made so far are fragmented within these disciplines, lacking connections and incurring potentially overlapping research activities in this subject area. The proposed book intends to bring together the advances in recent algorithmic developments, bridge the gaps between the methodologies adopted by the various disciplines, and overlook future directions in this subject.