ODAS: Open embeddeD Audition System
François Grondin, Dominic Létourneau, Cédric Godin, Jean-Samuel Lauzon, Jonathan Vincent, Simon Michaud, Samuel Faucher, François Michaud
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- github.com/introlab/odasnone★ 987
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.
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| . | YOLO | 0..5sec | 21 | — | Unverified |