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Teaching a robot to hear: A real-time on-board sound classification system for a humanoid robot

  • Western Sydney University

Research output: Chapter in Book / Conference PaperConference Paperpeer-review

2 Citations (Scopus)

Abstract

We present an approach for detecting, classi- fying and recognising novel non-verbal sounds on an Aldebaran Nao humanoid robot. Our method allows the robot to detect novel sounds, classify these sounds, and then recognise future instances. To learn the names of sounds, and whether each sound is relevant to the robot, a natural speech-based interaction occurs be- tween the robot and a human partner in which the robot seeks advice when a novel sound is heard. We test and demonstrate our system via an interactive human-robot game in which a person interacting with the robot can teach the robot via speech the names of novel sounds, and then test the robot's auditory classiffication and recognition capabilities by providing fur- ther examples of both novel sounds and sounds heard previously by the robot. The implemen- tation details of our acoustic sound recognition system are presented, together with empirical results describing the system's level of perfor- mance.

Original languageEnglish
Title of host publicationAustralasian Conference on Robotics and Automation, ACRA
PublisherAustralasian Robotics and Automation Association
ISBN (Electronic)9780980740448
Publication statusPublished - 2013
Event2013 Australasian Conference on Robotics and Automation, ACRA 2013 - Sydney, Australia
Duration: 2 Dec 20134 Dec 2013

Publication series

NameAustralasian Conference on Robotics and Automation, ACRA
ISSN (Print)1448-2053

Conference

Conference2013 Australasian Conference on Robotics and Automation, ACRA 2013
Country/TerritoryAustralia
CitySydney
Period2/12/134/12/13

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