Robot audition: Missing feature theory approach and active audition

Hiroshi G. Okuno, Kazuhiro Nakadai, Hyun Don Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)


Robot capability of listening to several things at once by its own ears, that is,robot audition, is important in improving interaction and symbiosis between humans and robots. The critical issue in robot audition is real-time processing and robustness against noisy environments with high flexibility to support various kinds of robots and hardware configurations. This paper presents two important aspects of robot audition; Missing-Feature-Theory (MFT) approach and active audition. HARK open-source robot audition incorporates MFT approach to recognize speech signals that are localized and separated from a mixture of sound captured by 8- channel microphone array. HARK is ported to four robots, Honda ASIMO, SIG2, Robovie-R2 and HRP-2, with different microphone configurations and recognizes three simultaneous utterances with 1.9 sec latency. In binaural hearing, the most famous problem is a front-back confusion of sound sources. Active binaural robot audition implemented on SIG2 disambiguates the problem well by rotating its head with pitting. This active audition improves the localization for the periphery.

Original languageEnglish
Title of host publicationSpringer Tracts in Advanced Robotics
Number of pages18
Publication statusPublished - 2011
Externally publishedYes
Event14th International Symposium of Robotic Research, ISRR 2009 - Lucerne
Duration: 2009 Aug 312009 Sept 3

Publication series

NameSpringer Tracts in Advanced Robotics
ISSN (Print)16107438
ISSN (Electronic)1610742X


Other14th International Symposium of Robotic Research, ISRR 2009

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Artificial Intelligence


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