Modeling individual vocal differences in group-living lemurs using vocal tract morphology

Abstract

Vocal individuality is widespread in social animals. Individual variation in vocalizations is a prerequisite for discriminating among conspecifics and may have facilitated the evolution of large complex societies. Ring-tailed lemurs Lemur catta live in relatively large social groups, have conspicuous vocal repertoires, and their species-specific utterances can be interpreted in light of source-filter theory of vocal production. Indeed, their utterances allow individual discrimination and even recognition thanks to the resonance frequencies of the vocal tract. The purpose of this study is to determine which distinctive vocal features can be derived from the morphology of the upper vocal tract. To accomplish this, we built computational models derived from anatomical measurements collected on lemur cadavers and compared the results with the spectrographic output of vocalizations recorded from ex situ live individuals. Our results demonstrate that the morphological variation of the ring-tailed lemur vocal tract explains individual distinctiveness of their species-specific utterances. We also provide further evidence that vocal tract modeling is a powerful tool for studying the vocal output of non-human primates.

Adherence to Menzerath's Law is the exception (not the rule) in three duetting primate species

“…Younger female white-handed gibbons produce long calls with a higher maximum frequency than older females, which may be related to age-related changes in the condition of the calling animal [ 42 ]. There is also substantial evidence for individual signatures in the duet contributions of indris [ 43 ], tarsier females [ 44 ], titi monkeys [ 45 ] and gibbons [ 46 – 48 ]. Although the function of duets remains a topic of debate [ 49 , 50 ], it is clear that duets are used to transmit information about the caller(s) to conspecifics over long distances.…”

Animal vocal communication: function, structures, and production mechanisms

“… Gamba et al (2017) demonstrate that morphological variation of the vocal tract shapes individual distinctiveness of the vocal utterances, and also provide further evidence that computational approaches can lead to a better understanding of the relationship between information encoding through individual signature and vocal anatomy.…”

Research on Modeling of Vocal State Duration Based on Spectrogram Analysis

“…The rapid conversion of analog signals to digital signals using computers is a way for students to visualize their voices on a computer screen. The computer displays the time, frequency, and intensity of sound occurring from the computer screen primarily through three-dimensional images; the y-axis represents the frequency spectrum, and the darker the grayscale, the stronger the intensity, and the lighter the grayscale, the weaker the intensity [4]. The spectrum is a two-dimensional image, usually with curves and data to represent the frequency and intensity of the sound.…”