Hidden Markov and Gaussian mixture models for automatic call classification

Judith C. Brown, Paris Smaragdis

Research output: Contribution to journalArticlepeer-review


Automatic methods of classification of animal sounds offer many advantages including speed and consistency in processing massive quantities of data. Calculations have been carried out on a set of 75 calls of Northern Resident killer whales, previously classified perceptually (human classification) into seven call types, using, hidden Markov models (HMMs) and Gaussian mixture models (GMMs). Neither of these methods has been used previously for classification of marine mammal call types. With cepstral coefficients as features both HMMs and GMMs give over 90% agreement with the perceptual classification, with the HMM over 95% for some cases.

Original languageEnglish (US)
Pages (from-to)EL221-EL224
JournalJournal of the Acoustical Society of America
Issue number6
StatePublished - 2009
Externally publishedYes

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Acoustics and Ultrasonics


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