The study of animal acoustic signals is a central tool for many fields in ecology and evolution, but the diversity of analytical methods and sources of animal sound recordings poses important challenges for carrying out robust acoustic analyses. Sound file compression and background noise may both affect acoustic analysis, although little attention has been paid to their respective effects. We evaluated the effect of these factors by assessing the systematic deviation (i.e. bias) and measurement error (i.e. precision) that they generate on spectrographic parameters and two (dis)similarity methods (dynamic time warping on frequency contours and cross-correlation), which represent the most common methods currently used for quantitative characterization of acoustic signals. Measurements were taken across a wide range of signals from a diverse group of bird species, and compared between uncompressed files and decompressed files obtained from mp3-encoded files generated using the two most common mp3 encoders (Fraunhofer and LAME). Measurements were also compared across a range of synthetically-generated background noise levels. Compression did not significantly bias any of the acoustic or similarity measurements. However, the precision of acoustic parameters representing single extreme values (e.g. peak frequency) as well as dynamic time warping distances, was strongly affected by compression. High background noise biased most energy distribution-related parameters (e.g. spectral entropy) and affected the precision of most acoustic parameters and dynamic time warping. Overall, compression and background noise did have considerable effects on acoustic analyses. We provide recommendations to avoid potential pitfalls and maximize the information that can be reliably obtained.
Sound file compression, mp3, acoustic analysis, dynamic-time warping, cross-correlation, spectrographic parameters