title: Template-based automatic recognition of birdsong syllables from continuous recordings.
abstract: The application of dynamic time warping (DTW) to the automated analysis of continuous recordings of animal vocalizations is evaluated. The DTW algorithm compares an input signal with a set of predefined templates representative of categories chosen by the investigator. It directly compares signal spectrograms, and identifies constituents and constituent boundaries, thus permitting the identification of a broad range of signals and signal components. When applied to vocalizations of an indigo bunting (Passerina cyanea) and a zebra finch (Taeniopygia guttata) collected from a low-clutter, low-noise environment, the recognizer identifies syllables in stereotyped songs and calls with greater than 97% accuracy. Syllables of the more variable and lower amplitude indigo bunting plastic song are identified with approximately 84% accuracy. Under restricted recordings conditions, this technique apparently has general applicability to analysis of a variety of animal vocalizations and can dramatically decrease the amount of time spent on manual identification of vocalizations.
authors: Department of Organismal Biology and Anatomy, University of Chicago, Illinois 60637, USA.
authors: S E
authors: SE
authors: Anderson
authors: A S
authors: AS
authors: Dave
authors: D
authors: D
authors: Margoliash
mesh_terms: D000818:Animals; D001307:Auditory Perception; D001717:Birds; D001330:Electronic Data Processing; D013018:Sound Spectrography; D013997:Time Factors; D014828:Vocalization, Animal