Template-based automatic recognition of birdsong syllables from continuous recordings. Academic Article uri icon

Overview

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.

publication date

  • August 1, 1996

Research

keywords

  • Auditory Perception
  • Vocalization, Animal

Identity

Scopus Document Identifier

  • 0029830701

PubMed ID

  • 8759970

Additional Document Info

volume

  • 100

issue

  • 2 Pt 1