Acoustic Complexity Index (ACI) from Pieretti, et al. 2011. The ACI is based on the "observation that many biotic sounds, such as bird songs, are characterized by an intrinsic variability of intensities, while some types of human generated noise (such as car passing or airplane transit) present very constant intensity values" (Pieretti, et al. 2011).
The index was tested to the ACItot calculated using SoundscapeMeter v 1.0.14.05.2012, courtesy of A. Farina.
The results given are accumulative. Very long samples will return very large values for ACI. I recommend to divide by number of minutes to get a range of values easier to compare.
acoustic_complexity(soundfile, min_freq = NA, max_freq = NA, j = 5, fft_w = 512)an object of class Wave loaded with the function readWave of the tuneR package.
miminum frequency to use when calculating the value, in Hertz. The default is NA.
maximum frequency to use when calculating the value, in Hertz. The default is the maximum for the file.
the cluster size, in seconds.
FFT window to use.
Returns a list with three objects per channel
the ACI total for the left channel
the ACI total for the right channel
the ACI total for the left channel divided by the number of minutes
the ACI total for the right channel divided by the number of minutes
values of ACI(fl) for the left channel
values of ACI(fl) for the right channel
Matrix of all values before calculating ACI(fl) for the left channel
Matrix of all values before calculating ACI(fl) for the right channel
Pieretti, N., A. Farina, and D. Morri. 2011. A new methodology to infer the singing activity of an avian community: The Acoustic Complexity Index (ACI). Ecological Indicators 11: 868-873. doi: 10.1016/j.ecolind.2010.11.005
# NOT RUN {
data(tropicalsound)
ACI <- acoustic_complexity(tropicalsound)
print(ACI$AciTotAll_left)
summary(ACI)
# }
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