Skip to page content
USDA Forest Service
  
Treesearch

Research & Development Treesearch

 
Treesearch Home
About Treesearch
Contact Us
Research & Development
Forest Products Lab
International Institute of Tropical Forestry
Northern
Pacific Northwest
Pacific Southwest
Rocky Mountain
Southern Research Station
Help
 

Science.gov - We Participate


USA.gov  Government Made Easy


Global Forest Information Service

US Forest Service
P.O. Box 96090
Washington, D.C.
20090-6090

(202) 205-8333

You are here: Home / Search / Publication Information
Bookmark and Share

Publication Information

View PDF (929 KB)

Title: Acoustic classification of multiple simultaneous bird species: a multi-instance multi-label approach

Author: Briggs, F.; Lakshminarayanan, B.; Neal, L.; Fern, X.Z.; Raich, R.; Hadley, S.F.; Hadley, A.S.; Betts, M.G.;

Date: 2012

Source: Acoustical Society of America. 131: 4640-4650

Publication Series: Scientific Journal (JRNL)

Description: Although field-collected recordings typically contain multiple simultaneously vocalizing birds of different species, acoustic species classification in this setting has received little study so far. This work formulates the problem of classifying the set of species present in an audio recording using the multi-instance multi-label (MIML) framework for machine learning, and proposes a MIML bag generator for audio, i.e., an algorithm which transforms an input audio signal into a bag-of-instances representation suitable for use with MIML classifiers. The proposed representation uses a 2D time-frequency segmentation of the audio signal, which can separate bird sounds that overlap in time. Experiments using audio data containing 13 species collected with unattended omnidirectional microphones in the H. J. Andrews Experimental Forest demonstrate that the proposed methods achieve high accuracy (96.1% true positives/negatives). Automated detection of bird species occurrence using MIML has many potential applications, particularly in long-term monitoring of remote sites, species distribution modeling, and conservation planning.

Keywords: birds, acoustic, multi-instance multi-label, H. J. Andrews Experimental Forest

Publication Notes:

  • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

XML: View XML

Citation:


Briggs, F.; Lakshminarayanan, B.; Neal, L.; Fern, X.Z.; Raich, R.; Hadley, S.F.; Hadley, A.S.; Betts, M.G. 2012. Acoustic classification of multiple simultaneous bird species: a multi-instance multi-label approach. Acoustical Society of America. 131: 4640-4650.

 


 [ Get Acrobat ]  Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility

USDA logo which links to the department's national site. Forest Service logo which links to the agency's national site.