Next Article in Journal
Behavioural Plasticity by Eastern Grey Kangaroos in Response to Human Behaviour
Previous Article in Journal
The Influence of Age on the Activity of Selected Biochemical Parameters of the Mouflon (Ovis musimon L.)
Previous Article in Special Issue
Future Directions for Personality Research: Contributing New Insights to the Understanding of Animal Behavior
Article Menu

Export Article

Open AccessArticle

Finding Meanings in Low Dimensional Structures: Stochastic Neighbor Embedding Applied to the Analysis of Indri indri Vocal Repertoire

1
Dipartimento di Scienze della Vita e Biologia dei Sistemi, Università degli Studi di Torino, 10123 Torino, Italy
2
Group d’Etude et de Recherche sur les Primates de Madagascar, Antananarivo 101, Madagascar
3
Mention d’Anthropobiologie et de Développement Durable (MADD), Université d’Antananarivo, Antananarivo 101, Madagascar
*
Author to whom correspondence should be addressed.
Animals 2019, 9(5), 243; https://doi.org/10.3390/ani9050243
Received: 31 March 2019 / Revised: 6 May 2019 / Accepted: 10 May 2019 / Published: 15 May 2019
(This article belongs to the Special Issue Proceedings of the 9th European Conference on Behavioural Biology)
  |  
PDF [1066 KB, uploaded 15 May 2019]
  |     |  

Simple Summary

The description of the vocal repertoire represents a critical step before deepening other aspects of animal behaviour. Repertoires may contain both discrete vocalizations—acoustically distinct and distinguishable from each other—or graded ones, with a less rigid acoustic structure. The gradation level is one of the causes that make repertoires challenging to be objectively quantified. Indeed, the higher the level of gradation in a system, the higher the complexity in grouping its components. A large sample of Indri indri calls was divided into ten putative categories from the acoustic similarity among them. We extracted frequency and duration parameters and then performed two different analyses that were able to group the calls accordingly to the a priori categories, indicating the presence of ten robust vocal classes. The analyses also showed a neat grouping of discrete vocalizations and a weaker classification of graded ones.

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 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. View Full-Text
Keywords: lemurs; vocal communication; unsupervised analyses lemurs; vocal communication; unsupervised analyses
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Valente, D.; De Gregorio, C.; Torti, V.; Miaretsoa, L.; Friard, O.; Randrianarison, R.M.; Giacoma, C.; Gamba, M. Finding Meanings in Low Dimensional Structures: Stochastic Neighbor Embedding Applied to the Analysis of Indri indri Vocal Repertoire. Animals 2019, 9, 243.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Animals EISSN 2076-2615 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top