The complexity of primates’ singing behavior has long gathered the attention of researchers interested in understanding the selective pressures underpinning the evolution of language. Among these pressures, a link between territoriality, pair-living, and singing displays has been suggested. Historically, singing primates have been found in a few taxa that are not closely related to each other, and, in the last years, their phylogeny has dramatically changed. Hence, we aimed at understanding if the dogmatic association between territorial behavior and a monogamous social structure still holds in the light of current research. Moreover, singing behavior has often been considered a whole, but animals can perform different singing forms depending on how many individuals call simultaneously. Currently, it is unclear to which extent these singing forms are widespread among these primate groups. Given that there is no unique definition for a “song”, “solo”, “duet”, and “chorus”, we envisioned some of the most used descriptions. We then formulated some new definitions that we followed in our review of the presence/absence of these different forms of song organization among singing primates’ taxa. In particular, we suggested that tarsier species that are typically considered non-singers may indeed sing, and we pointed out that non-duetting gibbons may perform duet interactions. We found that, besides duets, chorusing behavior and solo songs are essential features of primates’ communication, but their study is still in a descriptive phase. Moreover, while territorial behavior seems to be conserved in these singing taxa, we highlighted that the monogamous social structure is not the rule. Pair-living plus multi-females groups displaying singing behavior are common too. We suggest that ending to consider these taxa as uniform in their sociality and vocal behavior might be a significant turning point to unravel the different selective pressures that influenced the emergence and organization of such peculiar vocal behavior.

Estimating the number of animals participating in a choral display may contribute reliable information on animal population estimates, particularly when environmental or behavioral factors restrict the possibility of visual surveys. Difficulties in providing a reliable estimate of the number of singers in a chorus are many (e.g., background noise masking, overlap). In this work, we contributed data on the vocal chorusing of the indri lemurs (Indri indri), which emit howling cries, known as songs, uttered by two to five individuals. We examined whether we could estimate the number of emitters in a chorus by screening the fundamental frequency in the spectrograms and the total duration of the songs, and the reliability of those methods when compared to the real chorus size. The spectrographic investigation appears to provide reliable information on the number of animals participating in the chorusing only when this number is limited to two or three singers. We also found that the Acoustic Complexity Index positively correlated with the real chorus size, showing that an automated analysis of the chorus may provide information about the number of singers. We can state that song duration shows a correlation with the number of emitters but also shows a remarkable variation that remains unexplained. The accuracy of the estimates can reflect the high variability in chorus size, which could be affected by group composition, season and context. In future research, a greater focus on analyzing frequency change occurring during these collective vocal displays should improve our ability to detect individuals and allow a finer tuning of the acoustic methods that may serve for monitoring chorusing mammals.

Although there is a growing number of researches focusing on acoustic communication, the lack of shared analytic approaches leads to inconsistency among studies. Here, we introduced a computational method used to examine 3360 calls recorded from wild indris (Indri indri) from 2005–2018. We split each sound into ten portions of equal length and, from each portion we extracted spectral coefficients, considering frequency values up to 15,000 Hz. We submitted the set of acoustic features first to a t-distributed stochastic neighbor embedding algorithm, then to a hard-clustering procedure using a k-means algorithm. The t-distributed stochastic neighbor embedding (t-SNE) mapping indicated the presence of eight different groups, consistent with the acoustic structure of the a priori identification of calls, while the cluster analysis revealed that an overlay between distinct call types might exist. Our results indicated that the t-distributed stochastic neighbor embedding (t-SNE), successfully been employed in several studies, showed a good performance also in the analysis of indris’ repertoire and may open new perspectives towards the achievement of shared methodical techniques for the comparison of animal vocal repertoires.