Describing the sounds of nature: Using onomatopoeia to classify bird calls for citizen science

Bird call libraries are difficult to collect yet vital for bio-acoustics studies. A potential solution is citizen science labelling of calls. However, acoustic annotation techniques still relatively undeveloped and in parallel, initiatives struggle with maintaining participant engagement, while increasing efficiency accuracy. This study explores the use an under-utilised theoretically engaging intuitive means sound categorisation: onomatopoeia. To learn if onomatopoeia was a reliable categorisation, online experiment conducted. Participants sourced from Amazon mTurk (N = 104) ranked how well twelve onomatopoeic words described recordings ten native Australian bird Of calls, repeated measures ANOVA revealed that five these had single descriptors significantly higher than all others, remaining calls multiple were rated others. Agreement as assessed by Kendall’s W shows overall, raters agreed regarding suitability unsuitability used across Further analysis spread responses using frequency charts confirms this indicates agreement on which unsuitable pronounced throughout, stronger suitable singular descriptions matched greater rater confidence. demonstrates may be reliably classify non-expert listeners, adding suite methods classification biological sounds. Interface design implications discussed.