A statistical method for quantifying songbird phonology and syntax.
Songbirds are the preeminent animal model for understanding how the brain encodes and produces learned vocalizations. Here, we report a new statistical method, the Kullback-Leibler (K-L) distance, for analyzing vocal change over time. First, we use a computerized recording system to capture all song syllables produced by birds each day. Sound Analysis Pro software [Tchernichovski O, Nottebohm F, Ho CE, Pesaran B, Mitra PP. A procedure for an automated measurement of song similarity. Anim Behav 2000;59:1167-76] is then used to measure the duration of each syllable as well as four spectral features: pitch, entropy, frequency modulation, and pitch goodness. Next, two-dimensional scatter plots of each day of singing are created where syllable duration is on the x-axis and each of the spectral features is represented separately on the y-axis. Each point in the scatter plots represents one syllable and we regard these plots as random samples from a probability distribution. We then apply the standard information-theoretic quantity K-L distance to measure dissimilarity in phonology across days of singing. A variant of this procedure can also be used to analyze differences in syllable syntax.
Wu
Wei
W
Department of Statistics, Florida State University, Tallahassee, FL 32306-4330, USA. wwu@stat.fsu.edu
Thompson
John A
JA
Bertram
Richard
R
Johnson
Frank
F
D000162:Acoustics; D000465:Algorithms; D000818:Animals; D003627:Data Interpretation, Statistical; D003714:Denervation; D005010:Ethology / Q000379:methods*; D005260:Female; D046369:Finches / Q000502:physiology*; D053400:High Vocal Center / Q000502:physiology; D008297:Male; D009482:Neurophysiology / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D013061:Speech Acoustics; D014828:Vocalization, Animal / Q000502:physiology*