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      Automated bioacoustics: methods in ecology and conservation and their potential for animal welfare monitoring

      1 , 1 , 2

      Journal of The Royal Society Interface

      The Royal Society

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          Abstract

          <p class="first" id="d10111809e174">Vocalizations carry emotional, physiological and individual information. This suggests that they may serve as potentially useful indicators for inferring animal welfare. At the same time, automated methods for analysing and classifying sound have developed rapidly, particularly in the fields of ecology, conservation and sound scene classification. These methods are already used to automatically classify animal vocalizations, for example, in identifying animal species and estimating numbers of individuals. Despite this potential, they have not yet found widespread application in animal welfare monitoring. In this review, we first discuss current trends in sound analysis for ecology, conservation and sound classification. Following this, we detail the vocalizations produced by three of the most important farm livestock species: chickens ( <i>Gallus gallus domesticus</i>), pigs ( <i>Sus scrofa domesticus</i>) and cattle ( <i>Bos taurus</i>). Finally, we describe how these methods can be applied to monitor animal welfare with new potential for developing automated methods for large-scale farming. </p>

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          Most cited references 114

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          Acoustic monitoring in terrestrial environments using microphone arrays: applications, technological considerations and prospectus

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            Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification

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              Vocal expression of emotions in mammals: mechanisms of production and evidence

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                Author and article information

                Journal
                Journal of The Royal Society Interface
                J. R. Soc. Interface
                The Royal Society
                1742-5689
                1742-5662
                June 19 2019
                June 28 2019
                June 19 2019
                June 28 2019
                : 16
                : 155
                : 20190225
                Affiliations
                [1 ]Centre for Digital Music, School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Campus, London, UK
                [2 ]Centre for Research in Ecology, Evolution and Behaviour, Department of Life Sciences, University of Roehampton, London, UK
                Article
                10.1098/rsif.2019.0225
                6597774
                31213168
                © 2019

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