From collocations to call-ocations: using linguistic methods to quantify animal call combinations

Abstract

Emerging data in a range of non-human animal species have highlighted a latent ability to combine certain pre-existing calls together into larger structures. Currently, however, the quantification of context-specific call combinations has received less attention. This is problematic because animal calls can co-occur with one another simply through chance alone. One common approach applied in language sciences to identify recurrent word combinations is collocation analysis. Through comparing the co-occurrence of two words with how each word combines with other words within a corpus, collocation analysis can highlight above chance, two-word combinations. Here, we demonstrate how this approach can also be applied to non-human animal signal sequences by implementing it on artificially generated data sets of call combinations. We argue collocation analysis represents a promising tool for identifying non-random, communicatively relevant call combinations and, more generally, signal sequences, in animals. Significance statement Assessing the propensity for animals to combine calls provides important comparative insights into the complexity of animal vocal systems and the selective pressures such systems have been exposed to. Currently, however, the objective quantification of context-specific call combinations has received less attention. Here we introduce an approach commonly applied in corpus linguistics, namely collocation analysis, and show how this method can be put to use for identifying call combinations more systematically. Through implementing the same objective method, so-called call-ocations, we hope researchers will be able to make more meaningful comparisons regarding animal signal sequencing abilities both within and across systems.

Mapping vocal interactions in space and time differentiates signal broadcast versus signal exchange in meerkat groups

“…In 90% of cases, for any given call the next call was produced within 2.31 s ((median = 0.656 s; IQR =1 s)), so as a precaution towards excluding temporally independent signalling events, the upper 10% of the call transition times (>2.31 s) were omitted from subsequent analysis. To examine the occurrence of different call-category pairs we adopted the multiple distinctive collocation analysis (MDCA) described in Bosshard et al [49] and used it for quantifying ‘collocations’ (grammatical constructions) in human [50] and animal [51] communication. Briefly, the method calculates binomial probabilities for every possible call category combination (accounting for sample size) and log-transforms them for estimation of under- or over-representative combinations (the greater the value, the stronger the association between call categories in the combination).…”