This thesis makes two claims. First, it claims that machine listening technologies are well-suited to the task of providing context awareness in real-world computational systems, whether these systems are intended to provide operational cues to smart devices or spaces, or to segment, summarize, or select segments of interest in multimedia corpora to make them more useful to human users. Second, it claims that the use of the core principle of perception, redundancy reduction, can guide the design of practical systems to provide context awareness in this way. The validity of these claims is supported by evidence from three application areas: multimedia gisting, acoustic environment recognition, and estimation of user interruptibility for the CHIL Connector service, a smart mobile telephone.
