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 recording 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.
Original language | English (US) |
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Pages (from-to) | 1209-1219 |
Number of pages | 11 |
Journal | Journal of the Acoustical Society of America |
Volume | 100 |
Issue number | 2 I |
DOIs | |
State | Published - Aug 1996 |
ASJC Scopus subject areas
- Arts and Humanities (miscellaneous)
- Acoustics and Ultrasonics