  Artificial audition aims at providing hearing capabilities to machines,
computers and robots. Existing frameworks in robot audition offer interesting
sound source localization, tracking and separation performance, although
involve a significant amount of computations that limit their use on robots
with embedded computing capabilities. This paper presents ODAS, the Open
embeddeD Audition System framework, which includes strategies to reduce the
computational load and perform robot audition tasks on low-cost embedded
computing systems. It presents key features of ODAS, along with cases
illustrating its uses in different robots and artificial audition applications.
