Article: Evaluation of acoustic pattern recognition of nightingale (Luscinia megarhynchos) recordings by citizens
Research Ideas and Outcomes. 2020 Feb. 24, v. 6
2020
Abstract: Acoustic pattern recognition methods introduce new perspectives for species identification, biodiversity monitoring and data validation in citizen science but are rarely evaluated in real world scenarios. In this case study we analysed the performance of ...
Abstract | Acoustic pattern recognition methods introduce new perspectives for species identification, biodiversity monitoring and data validation in citizen science but are rarely evaluated in real world scenarios. In this case study we analysed the performance of a machine learning algorithm for automated bird identification to reliably identify common nightingales (Luscinia megarhynchos) in field recordings taken by users of the smartphone app Naturblick. We found that the performance of the automated identification tool was overall robust in our selected recordings. Although most of the recordings had a relatively low confidence score, a large proportion of the recordings were identified correctly. |
---|---|
Keywords | Luscinia ; acoustics ; algorithms ; automation ; biodiversity ; birds ; case studies ; citizen science ; mobile telephones ; research ; species identification |
Language | English |
Dates of publication | 2020-0224 |
Publishing place | Pensoft Publishers |
Document type | Article |
ZDB-ID | 2833254-4 |
ISSN | 2367-7163 |
ISSN | 2367-7163 |
DOI | 10.3897/rio.6.e50233 |
Database | NAL-Catalogue (AGRICOLA) |
More links
Kategorien
Order via subito
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.