  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, but 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.
