Acoustic environment classification

Ma, Ling, Milner, Ben P. and Smith, Dan J. (2006) Acoustic environment classification. ACM Transactions on Speech and Language Processing, 3 (2). pp. 1-22. ISSN 1550-4875

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Abstract

The acoustic environment provides a rich source of information on the types of activity, communication modes, and people involved in many situations. It can be accurately classified using recordings from microphones commonly found in PDAs and other consumer devices. We describe a prototype HMM-based acoustic environment classifier incorporating an adaptive learning mechanism and a hierarchical classification model. Experimental results show that we can accurately classify a wide variety of everyday environments. We also show good results classifying single sounds, although classification accuracy is influenced by the granularity of the classification.

Item Type:	Article
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Interactive Graphics and Audio Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Data Science and AI
Depositing User:	Vishal Gautam
Date Deposited:	08 Mar 2011 10:41
Last Modified:	10 Dec 2024 01:20
URI:	https://ueaeprints.uea.ac.uk/id/eprint/22647
DOI:	10.1145/1149290.1149292

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