Table 1. Measured acoustical variables.

Measurements based on the Raven Pro manual (Charif, Waack & Strickman, 2010).

(LowF) Low frequency.Minimum frequency of the signal. (Hz)
(CF) Center frequency.The frequency that divides a signal into two frequency intervals of equal energy. (Hz)
(Q1F) First quartile frequency.The frequency that divides the signal into two frequency intervals containing 25% and 75% of the energy. (Seconds)
(Q3F) Third quartile frequency.The frequency that divides the selection into two frequency intervals containing 75% and 25% of the energy. (Hz)
(Q1T) First quartile time.The point in time that divides the selection into two time intervals containing 25% and 75% of the energy. (Seconds)
(Q3T) Third quartile time.The point in time that divides the selection into two time intervals containing 75% and 25% of the energy. (Seconds)
(T95) Time 95%.The point in time that divides the signal into two time intervals containing 95% and 5% of the energy. (Seconds)
(T5) Time 5%.The point in time that divides the signal into two time intervals containing 5% and 95% of the energy. (Seconds)
(Call duration) Sample length. Signal duration based on sample length. (Samples)
(F5) Frequency 5%.The frequency that divides the signal into two frequency intervals containing 5% and 95% of the energy. (Hz)
(F95) Frequency 95%. The frequency that divides the selection into two frequency intervals containing 95% and 5% of the energy in the selection. (Hz)
(BW90) Bandwidth 90%.The difference between the 5% and 95% frequencies. (Hz)
(IQR) Inter-quartile range.The difference between the 1st and 3rd quartile frequencies. (Hz).
(PeakF) Peak frequency.Frequency of the maximum amplitude. (Hz)
(AggE) Aggregate Entropy. The aggregate entropy measures the disorder in a sound by analyzing the energy. Higher values correspond to greater disorder in the signal whereas a pure tone have zero entropy. It corresponds to the overall disorder in the sound.
(MinE) Minimum Entropy. This entropy is calculated by finding the entropy for each frame in the signal and then taking the minimum values.
The entropy formula: S = PSD(f, t)∕sum_over_f(PSD(f, t))∗log2(PSD(f, t)∕sum_over_f(PSD(f, t)))
The units are “bits” because we use the log base 2. Since the selection may consist of multiple spectrogram slices, Raven iterates over slices and to find the minimum and maximum entropy value with the frequency bounds of the selection. Note that most signal processing applications sum over frequency and time, where Raven sums over frequency instead.