ODAS: Open embeddeD Audition System

TL;DR

ODAS is an open-source framework designed to enable robot audition on low-cost embedded systems by reducing computational load while maintaining sound source localization, tracking, and separation capabilities.

Contribution

It introduces strategies to lower computational requirements for robot audition tasks, making advanced auditory processing feasible on embedded systems.

Findings

Effective reduction in computational load demonstrated

Supports various robots and audition applications

Maintains core auditory functionalities on embedded hardware

Abstract

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.