Cepstral coefficients and hidden Markov models reveal idiosyncratic voice characteristics in red deer (Cervus elaphus) stags

Bouts of vocalizations given by seven red deer stags were recorded over the rutting period, and homomorphic analysis and hidden Markov models (two techniques typically used for the automatic recognition of human speech utterances) were used to investigate whether the spectral envelope of the calls was individually distinctive. Bouts of common roars (the most common call type) were highly individually distinctive, with an average recognition percentage of 93.5%. A "temporal" split-sample approach indicated that although in most individuals these identity cues held over the rutting period, the ability of the models trained with the bouts of roars recorded early in the rut to correctly classify later vocalizations decreased as the recording date increased. When Markov models trained using the bouts of common roars were used to classify other call types according to their individual membership, the classification results indicated that the cues to identity contained in the common roars were also present in the other call types. This is the first demonstration in mammals other than primates that individuals have vocal cues to identity that are common to the different call types that compose their vocal repertoire.