ACI: Acoustic Complexity Index

In seewave: Sound Analysis and Synthesis

Acoustic Complexity Index

Description

This function computes the Acoustic Complexity Index (ACI) as described in Pieretti et al. (2011)

Usage

ACI(wave, f, channel = 1, wl = 512, ovlp = 0,  wn = "hamming", flim = NULL, nbwindows = 1)

Arguments

wave	an R object.
f	sampling frequency of wave (in Hz). Does not need to be specified if embedded in wave.
channel	channel of the R object, by default left channel (1).
wl	window length for the analysis (even number of points) (by default = 512).
ovlp	overlap between two successive windows (in %).
wn	window name, see ftwindow (by default "hanning").
flim	a numeric vector of length 2 to select a frequency band (in kHz).
nbwindows	a numeric vector of length 1 specifying the number of windows (by default 1, ie a single window including the complete wave object.

Details

The function computes first a short-term Fourier transform and then the ACI index.
The function returns only the ACI total, ACI tot in Pieretti et al. (2010).
See the references for details on computation.

Value

A vector of length 1 returning the ACI total.

Note

Values returned were checked with the results provided by the add-on Soundscapemeter for the software Wavesurfer.

Author(s)

Laurent Lellouch, improved by Amandine Gasc and Morgane Papin

References

Pieretti N, Farina A, Morri FD (2011) A new methodology to infer the singing activity of an avian community: the Acoustic Complexity Index (ACI). Ecological Indicators, 11, 868-873.
Farina A, Pieretti N, Piccioli L (2011) The soundscape methodology for long-term bird monitoring: a Mediterranean Europe case-study. Ecological Informatics, 6, 354-363.

See Also

spectro, specflux

Examples

data(tico)
ACI(tico)
## dividing the sound sample into 4 windows of equal duration
ACI(tico, nbwindows=4)
## selection of a frequency band
ACI(tico, flim=c(2,6))

seewave documentation built on Oct. 19, 2023, 5:07 p.m.