Multi-stage classification for audio based activity recognition

  • Authors:
  • José Lopes;Charles Lin;Sameer Singh

  • Affiliations:
  • Research School of Informatics, Loughborough University, Loughborough, UK;Research School of Informatics, Loughborough University, Loughborough, UK;Research School of Informatics, Loughborough University, Loughborough, UK

  • Venue:
  • IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
  • Year:
  • 2006

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Abstract

Context recognition in indoor and outdoor surroundings is an important area of research for the development of autonomous systems. This work describes an approach to the classification of audio signals found in both indoor and outdoor environments. Several audio features are extracted from raw signals. We analyze the relevance and importance of these features and use that information to design a multi-stage classifier architecture. Our results show that the multi-stage classification scheme is superior than a single stage classifier and it generates an 80% success rate on a 7 class problem.