pp 1–9 | Cite as

Automated classification of bees and hornet using acoustic analysis of their flight sounds

  • Satoshi KawakitaEmail author
  • Kotaro Ichikawa
Original article


To investigate how to accurately identify bee species using their sounds, we conducted acoustic analysis to identify three pollinating bee species (Apis mellifera, Bombus ardens, Tetralonia nipponensis) and a hornet (Vespa simillima xanthoptera) by their flight sounds. Sounds of the insects and their environment (background noises and birdsong) were recorded in the field. The use of fundamental frequency and mel-frequency cepstral coefficients to describe feature values of the sounds, and supported vector machines to classify the sounds, correctly distinguished sound samples from environmental sounds with high recalls and precision (0.96–1.00). At the species level, our approach could classify the insect species with relatively high recalls and precisions (0.7–1.0). The flight sounds of V.s. xanthoptera, in particular, were perfectly identified (precision and recall 1.0). Our results suggest that insect flight sounds are potentially useful for detecting bees and quantifying their activity.


species classification Hymenoptera machine learning acoustic analysis 



We thank Dr. Fumio Sakamoto and Dr. Junichiro Abe for supporting our experiments and giving us the opportunity to record the flight sounds of insects.

Authors’ contribution

SK conceived the research; KI participated in the design and interpretation of the data; SK performed experiments and analysis. Both authors wrote the paper and approved the final manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest

Supplementary material

13592_2018_619_MOESM1_ESM.wav (140 kb)
Flight sound sample of A. mellifera (WAV 140 kb)
13592_2018_619_MOESM2_ESM.wav (48 kb)
Flight sound sample of B. ardens (WAV 48 kb)
13592_2018_619_MOESM3_ESM.wav (57 kb)
Flight sound sample of T. nipponensis (WAV 56 kb)
13592_2018_619_MOESM4_ESM.wav (91 kb)
Flight sound sample of V. s. xanthoptera (WAV 90 kb)


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Copyright information

© INRA, DIB and Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Western Region Agricultural Research CenterNational Agriculture and Food Research OrganizationHiroshimaJapan
  2. 2.Field Science Education and Research CenterKyoto UniversityKyotoJapan

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