title: Automatic identification of individual killer whales.
abstract: Following the successful use of HMM and GMM models for classification of a set of 75 calls of northern resident killer whales into call types [Brown, J. C., and Smaragdis, P., J. Acoust. Soc. Am. 125, 221-224 (2009)], the use of these same methods has been explored for the identification of vocalizations from the same call type N2 of four individual killer whales. With an average of 20 vocalizations from each of the individuals the pairwise comparisons have an extremely high success rate of 80 to 100% and the identifications within the entire group yield around 78%.
authors.affiliation: Department of Physics, Wellesley College, Wellesley, Massachusetts 02481, USA. brown@media.mit.edu
authors.forename: Judith C
authors.initials: JC
authors.lastname: Brown
authors.forename: Paris
authors.initials: P
authors.lastname: Smaragdis
authors.forename: Anna
authors.initials: A
authors.lastname: Nousek-McGregor
mesh_terms: D000465:Algorithms; D000818:Animals; D001331:Automation; D008390:Markov Chains; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography; D013997:Time Factors; D014828:Vocalization, Animal; D050685:Whale, Killer / Q000502:physiology*