Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well-known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise – let alone understand – the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near-future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, “Analysing vocal sequences in animals”. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial-style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.

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Thresholds for detecting alterations in the timbre and harmonicity of complex harmonic signals were measured in zebra finches, budgerigars, and humans. The stimuli used in this experiment were designed to have particular salience for zebra finches by modeling them after natural zebra finch calls. All 3 species showed similar abilities for detecting an amplitude decrement in a single component of a harmonic complex. However, zebra finches and budgerigars were extraordinarily sensitive to the mistunings of single harmonics and exhibited significantly lower thresholds compared with humans at 2 different fundamental frequencies, 570 Hz and 285 Hz. Randomizing relative phases of components in a harmonic stimulus resulted in a significant increase in threshold for detecting mistunings in zebra finches but not in humans. Decreasing the duration of mistuned harmonic stimuli resulted in higher thresholds for both birds and humans. The overall superiority of birds in discriminating inharmonicity suggests that birds and mammals may use different strategies in processing these complex harmonic sounds.

The auditory brainstem response (ABR), a measure of neural synchrony, was used to estimate auditory sensitivity in the eastern screech owl (Megascops asio). The typical screech owl ABR waveform showed two to three prominent peaks occurring within 5 ms of stimulus onset. As sound pressure levels increased, the ABR peak amplitude increased and latency decreased. With an increasing stimulus presentation rate, ABR peak amplitude decreased and latency increased. Generally, changes in the ABR waveform to stimulus intensity and repetition rate are consistent with the pattern found in several avian families. The ABR audiogram shows that screech owls hear best between 1.5 and 6.4 kHz with the most acute sensitivity between 4-5.7 kHz. The shape of the average screech owl ABR audiogram is similar to the shape of the behaviorally measured audiogram of the barn owl, except at the highest frequencies. Our data also show differences in overall auditory sensitivity between the color morphs of screech owls.