Detection and identification of beehive piping audio signals
Résumé
Piping signals are particular sounds emitted by honey bees during the swarming season or sometimes when bees are exposed to specific factors during the life of the colony. Such sounds are of interest for beekeepers for predicting an imminent swarming of a beehive. The present study introduces a novel publicly available dataset made of several honey bee piping recordings allowing for the evaluation of future audio-based detection and recognition methods. First, we propose an analysis of the most relevant timbre features for discriminating between tooting and quacking sounds which are two distinct types of piping signals. Second, we comparatively assess several machine-learning-based methods designed for the detection and the identification of piping signals through a beehiveindependent 3-fold cross-validation methodology.
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