Abstract: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 s… Show more
“…Figure 1Rhythm and social interactions in indris. ( a ) A spectrogram of a vocal interaction between two males from the same family group that compete for food; the adult male emits a low-pitched grunt [84] followed by a kiss and a wheeze from the younger male [85]. ( c ) A spectrogram of part of an unusual solo song by a male indri.…”
This review paper discusses
rhythmic
interactions and distinguishes them from
non-rhythmic
interactions. We report on communicative behaviours in social and sexual contexts, as found in dyads of humans, non-human primates, non-primate mammals, birds, anurans and insects. We discuss observed instances of rhythm in dyadic interactions, identify knowledge gaps and propose suggestions for future research. We find that most studies on rhythmicity in interactive signals mainly focus on one modality (acoustic or visual) and we suggest more work should be performed on multimodal signals. Although the social functions of interactive rhythms have been fairly well described, developmental research on rhythms used to regulate social interactions is still lacking. Future work should also focus on identifying the exact timing mechanisms involved. Rhythmic signalling behaviours are widespread and critical in regulating social interactions across taxa, but many questions remain unexplored. A multidisciplinary, comparative cross-species approach may help provide answers.
This article is part of the theme issue ‘Synchrony and rhythm interaction: from the brain to behavioural ecology’.
“…Figure 1Rhythm and social interactions in indris. ( a ) A spectrogram of a vocal interaction between two males from the same family group that compete for food; the adult male emits a low-pitched grunt [84] followed by a kiss and a wheeze from the younger male [85]. ( c ) A spectrogram of part of an unusual solo song by a male indri.…”
This review paper discusses
rhythmic
interactions and distinguishes them from
non-rhythmic
interactions. We report on communicative behaviours in social and sexual contexts, as found in dyads of humans, non-human primates, non-primate mammals, birds, anurans and insects. We discuss observed instances of rhythm in dyadic interactions, identify knowledge gaps and propose suggestions for future research. We find that most studies on rhythmicity in interactive signals mainly focus on one modality (acoustic or visual) and we suggest more work should be performed on multimodal signals. Although the social functions of interactive rhythms have been fairly well described, developmental research on rhythms used to regulate social interactions is still lacking. Future work should also focus on identifying the exact timing mechanisms involved. Rhythmic signalling behaviours are widespread and critical in regulating social interactions across taxa, but many questions remain unexplored. A multidisciplinary, comparative cross-species approach may help provide answers.
This article is part of the theme issue ‘Synchrony and rhythm interaction: from the brain to behavioural ecology’.
“…Indris ( Indri indri ; Gmelin, 1788) represent a distinctive species for studying vocal communication because of their rich repertoire (Maretti, Sorrentino, Finomana, Gamba, & Giacoma, 2010; Valente et al, 2019) and the impressive loud songs, unique among lemurs (Gamba et al, 2016; Torti et al, 2017), which can be heard at a distance up to 2 km (Pollock, 1986). Data on sound pressure levels revealed that the sound levels of the indri's song reached 110 dB (estimated at 0.50 m; Torti, pers.…”
Section: Introductionmentioning
confidence: 99%
“…The song of the indris, which lasts 40–250 s, consists of a long series of modulated units, organized in phrases (Gamba, Favaro, Torti, Sorrentino, & Giacoma, 2011), uttered simultaneously by males and females, including juveniles, of the same group (Maretti et al, 2010). These types of units are emitted exclusively during the song (Valente et al, 2019).…”
Animal acoustic communication often takes the form of complex sequences, composed of multiple distinct acoustic units, which can vary in their degree of stereotypy.Studies of sequence variation may contribute to our understanding of the structural flexibility of primates' songs, which can provide essential ecological and behavioral information about variability at the individual, population, and specific level and provide insights into the mechanisms and drivers responsible for the evolutionary change of communicative traits. Several methods have been used for investigating different levels of structural information and sequence similarity in acoustic displays. We studied intra and interindividual variation in the song structuring of a singing primate, the indri (Indri indri), which inhabits the montane rain forests of Madagascar. Indri groups emit duets and choruses in which they combine long notes, short single units, and phrases consisting of a variable number of units (from two to six) with slightly descending frequency. Males' and females' contributions to the song differ in the temporal and frequency structure of song units and repertoire size. We calculated the similarity of phrase organization across different individual contributions using the Levenshtein distance, a logic distance that expressed the minimum cost to convert a sequence into another and can measure differences between two sequences of data. We then analyzed the degree of similarity within and between individuals and found that: (a) the phrase structure of songs varied between reproductive males and females: female structuring of the song showed a higher number of phrases if compared to males; (b) male contributions to the song were overall more similar to those of other males than were female contributions to the song of other females; (c) male contributions were more stereotyped than female contributions, which showed greater individual flexibility.The picture emerging from phrase combinatorics in the indris is in agreement with previous findings of rhythmic features and song repertoire size of the indris, which also suggested that female songs are potentially less stereotyped than those of males.
K E Y W O R D Slanguage evolution, Levenshtein distance, primates, singing, syntax
“…Most unsupervised applications related to non‐human primate vocalizations have investigated species‐specific call repertoires (Keenan et al., 2013; Pozzi et al., 2009; Price et al., 2015; Valente et al., 2019; Wadewitz et al., 2015). One of the foundational applications of unsupervised clustering was used to investigate the vocal repertoire of Barbary macaques Macaca sylvanus (Hammerschmidt & Fischer, 1998).…”
Section: Introductionmentioning
confidence: 99%
“…One of the foundational applications of unsupervised clustering was used to investigate the vocal repertoire of Barbary macaques Macaca sylvanus (Hammerschmidt & Fischer, 1998). Since then, unsupervised approaches have been used to investigate vocal repertoires in indris Indri indri (Valente et al., 2019), black lemurs Eulemur macaco (Pozzi et al., 2009), Eulemur spp. (Gamba et al., 2015), marmosets Callithrix jacchus (Turesson et al., 2016), douc langurs Pygathrix cinerea (Riondato et al., 2017), Campbells's monkeys Cercopithecus campbelli (Keenan et al., 2013), chacma Papio ursinus , olive P. anubis and Guinea baboons P. papio (Hammerschmidt & Fischer, 2019) and gorillas Gorilla gorilla (Hedwig et al., 2014).…”
Passive acoustic monitoring (PAM) has the potential to greatly improve our ability to monitor cryptic yet vocal animals. Advances in automated signal detection have increased the scope of PAM, but distinguishing between individuals—which is necessary for density estimation—remains a major challenge. When individual identity is known, supervised classification techniques can be used to distinguish between individuals. Supervised methods require labelled training data, whereas unsupervised techniques do not. If the acoustic signals of individuals are sufficiently different, the number of clusters might represent the number of individuals sampled. The majority of applications of unsupervised techniques in animal vocalizations have focused on quantifying species‐specific call repertoires. However, with increased interest in PAM applications, unsupervised methods that can distinguish between individuals are needed.
Here we use an existing dataset of Bornean gibbon female calls with known identity from five sites on Malaysian Borneo to test the ability of three different unsupervised clustering algorithms (affinity propagation, K‐medoids and Gaussian mixture model‐based clustering) to distinguish between individuals. Calls from different gibbon females are readily distinguishable using supervised techniques. For internal validation of unsupervised cluster solutions, we calculated silhouette coefficients. For external validation, we compared clustering results with female identity labels using a standard metric: normalized mutual information. We also calculated classification accuracy by assigning unsupervised cluster solutions to females based on which cluster had the highest number of calls from a particular female.
We found that affinity propagation clustering consistently outperformed the other algorithms for all metrics used. In particular, classification accuracy of affinity propagation clustering was more consistent as the number of females increased, and when we randomly sampled females across sites.
We conclude that unsupervised techniques may be useful for providing additional information regarding individual identity for PAM applications. We stress that although we use gibbons as a case study, these methods will be applicable for any individually distinct vocal animal.
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