The Acoustic Complexity Index (ACI) is one of the most used metrics in ecoacoustics, demonstrating reliability across a broad range of environments and ecological conditions. However, this index requires specific procedures to be applied in the correct way. Based on the “Canberra metric,” the ACI is an unsupervised metric formulated to extract information from fast Fourier transform (FFT) sonic matrices. The ACI measures contiguous differences in acoustic energy of each frequency bin i along temporal steps (ACItf) and of a temporal interval j along the frequency bins (ACIft). The aggregation of data after an FFT using a clumping procedure allows for better scaling of the sonic signals before the computation of the ACI. The application of a filter to reduce the effects of non-environmental signals produced by microphone electrical noise is mandatory to avoid masking effects. Due to a singularity of the index for values equal to 0, ACIs require ad hoc procedures to exclude from the comparisons pairs of elements of which one is equal to 0. The spectral sonic signature and temporal sonic signature are vectors obtained from the sequence of ACItf and ACIft values, respectively. The comparison between sonic signatures using the chord distance index returns spectral and temporal sonic dissimilarities that allow the evaluation of sonic patterns emerging at different temporal and spatial resolutions. The number of frequency bins, sonic variability, and sonic evenness are further derivative metrics that help to interpret sonic heterogeneity by distinguishing the temporal and spatial heterogeneity of sonoscapes. A change of the name of the “Acoustic Complexity Index” to the “Sonic Heterogeneity Index” is recommended.