A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
A Successful Crowdsourcing Approach for Bird Sound Classification (2023)

Lehikoinen, P., Rannisto, M., Camargo, U., Aintila, A., Lauha, P., Piirainen, E., Somervuo, P., & Ovaskainen, O. (2023). A Successful Crowdsourcing Approach for Bird Sound Classification. Citizen science, 8(1), 1-14. https://doi.org/10.5334/cstp.556

JYU-tekijät tai -toimittajat

Ovaskainen, Otso

Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Lehikoinen, Petteri; Rannisto, Meeri; Camargo, Ulisses; Aintila, Aki; Lauha, Patrik; Piirainen, Esko; Somervuo, Panu; Ovaskainen, Otso

Lehti tai sarja: Citizen science

eISSN: 2057-4991

Julkaisuvuosi: 2023

Ilmestymispäivä: 11.04.2023

Volyymi: 8

Lehden numero: 1

Artikkelin sivunumerot: 1-14

Kustantaja: Ubiquity Press, Ltd.

Julkaisumaa: Britannia

Julkaisun kieli: englanti

DOI: https://doi.org/10.5334/cstp.556

Julkaisun avoin saatavuus: Avoimesti saatavilla

Julkaisukanavan avoin saatavuus: Kokonaan avoin julkaisukanava

Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/86539

Tiivistelmä

Automated recorders are increasingly used in remote sensing of wildlife, yet automated methods of processing the audio remains challenging. Identifying animal sounds with machine learning provides a solution, but optimizing the models requires annotated training data. Producing such data can require much manual effort, which could be alleviated by engaging masses to contribute to research and share the workload. Birdwatchers are experts on identifying bird vocalizations and form an ideal focal audience for a citizen science project aiming for the required multitudes of annotated avian audio data. For this purpose, we launched a web portal that was targeted and advertised to Finnish birdwatchers. The users were asked to complete two kinds of tasks: 1) classify if a given bird sound belonged to the focal species and 2) classify all the bird species vocalizing in 10-second audio clips. In less than a year, the portal achieved annotations for 244,300 bird sounds and 5,358 clips, and attracted, on average, 70 visitors on daily basis. More than 200 birdwatchers took part in the classification tasks, of which 17 and 4 most dedicated users produced over half of the sound and clip classifications, respectively. As expected of birder experts, the classifications among users were highly consistent (mean agreement scores between 0.85–0.95, depending on the audio type) and resulted in highquality training data for parameterizing machine learning models. Feedback about the web portal suggested that additional functionality such as increased freedom of choice would increase user motivation and dedication.

YSO-asiasanat: lintutiede; kansalaistiede; koneoppiminen; portaalit (tietotekniikka); tunnistaminen; eläinten äänet

Vapaat asiasanat: citizen science; machine learning; bioacoustics; ornithology; web portal

Liittyvät organisaatiot

Hankkeet, joissa julkaisu on tehty

OKM-raportointi: Kyllä

Raportointivuosi: 2023

Alustava JUFO-taso: 2