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

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

    Abstract

    We present an approach for detecting, classifying 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 classification and recognition capabilities by providing further examples of both novel sounds and sounds heard previously by the robot. The implementation details of our acoustic sound recognition system are presented, together with empirical results describing the system's level of performance.
    Original languageEnglish
    Title of host publicationProceedings of Australasian Conference on Robotics and Automation (ACRA2013), 2-4 Dec 2013, University of New South Wales, Sydney, Australia
    PublisherAustralian Robotics and Automation Association
    Pages438-445
    Number of pages8
    ISBN (Print)9781632660275
    Publication statusPublished - 2013
    EventAustralasian Conference on Robotics and Automation -
    Duration: 2 Dec 2013 → …

    Conference

    ConferenceAustralasian Conference on Robotics and Automation
    Period2/12/13 → …

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