Pitch- and spectral-based dynamic time warping methods for comparing field recordings of harmonic avian vocalizations.
Quantitative measures of acoustic similarity can reveal patterns of shared vocal behavior in social species. Many methods for computing similarity have been developed, but their performance has not been extensively characterized in noisy environments and with vocalizations characterized by complex frequency modulations. This paper describes methods of bioacoustic comparison based on dynamic time warping (DTW) of the fundamental frequency or spectrogram. Fundamental frequency is estimated using a Bayesian particle filter adaptation of harmonic template matching. The methods were tested on field recordings of flight calls from superb starlings, Lamprotornis superbus, for how well they could separate distinct categories of call elements (motifs). The fundamental-frequency-based method performed best, but the spectrogram-based method was less sensitive to noise. Both DTW methods provided better separation of categories than spectrographic cross correlation, likely due to substantial variability in the duration of superb starling flight call motifs.
Department of Organismal Biology and Anatomy, University of Chicago, 1027 East 57th Street, Chicago, Illinois 60622, USA. dmeliza@uchicago.edu
C Daniel
CD
Meliza
Sara C
SC
Keen
Dustin R
DR
Rubenstein
D000162:Acoustics; D000465:Algorithms; D000818:Animals; D001499:Bayes Theorem; D005426:Flight, Animal; D010363:Pattern Recognition, Automated; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography; D046749:Starlings / Q000502:physiology*; D013997:Time Factors; D014828:Vocalization, Animal