Discrimination of individual tigers (Panthera tigris) from long distance roars

An Ji, Michael T. Johnson, Edward J. Walsh, Joann McGee, Douglas L. Armstrong

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

This paper investigates the extent of tiger (Panthera tigris) vocal individuality through both qualitative and quantitative approaches using long distance roars from six individual tigers at Omaha's Henry Doorly Zoo in Omaha, NE. The framework for comparison across individuals includes statistical and discriminant function analysis across whole vocalization measures and statistical pattern classification using a hidden Markov model (HMM) with frame-based spectral features comprised of Greenwood frequency cepstral coefficients. Individual discrimination accuracy is evaluated as a function of spectral model complexity, represented by the number of mixtures in the underlying Gaussian mixture model (GMM), and temporal model complexity, represented by the number of sequential states in the HMM. Results indicate that the temporal pattern of the vocalization is the most significant factor in accurate discrimination. Overall baseline discrimination accuracy for this data set is about 70% using high level features without complex spectral or temporal models. Accuracy increases to about 80% when more complex spectral models (multiple mixture GMMs) are incorporated, and increases to a final accuracy of 90% when more detailed temporal models (10-state HMMs) are used. Classification accuracy is stable across a relatively wide range of configurations in terms of spectral and temporal model resolution.

Original languageEnglish
Pages (from-to)1762-1769
Number of pages8
JournalJournal of the Acoustical Society of America
Volume133
Issue number3
DOIs
StatePublished - Mar 2013

Bibliographical note

Funding Information:
The authors would like to thank Adam Smith, Amy Larson, Ian Hoppe, Joseph Churilla, Alisa Theis, and staff of the Henry Doorly Zoo for their important contributions to the study. Work reported here was partially supported by the National Science Foundation Grant No. IOS 0823417.

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Acoustics and Ultrasonics

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