Publication
A Human-in-the-Loop Tool for Annotating Passive Acoustic Monitoring Datasets\\(Extended Abstract)
Hannes Kath; Thiago Gouvea; Daniel Sonntag
In: Dietmar Seipel; Alexander Steen (Hrsg.). KI 2024: Advances in Artificial Intelligence. German Conference on Artificial Intelligence (KI-2024), 47th German Conference on AI, Würzburg, Germany, September 25–27, 2023, Proceedings, located at 47th German Conference on AI, September 25-27, Würzburg, Germany, Germany, LNAI, Springer, Heidelberg, 9/2024.
Abstract
Passive Acoustic Monitoring (PAM) has become a key technology in wildlife monitoring, generating large amounts of acoustic data. However, the effective application of machine learning methods for sound event detection in PAM datasets is highly dependent on the availability of annotated data, which requires a labour-intensive effort to generate. This paper summarises two iterative, human-centred approaches that make efficient use of expert annotation time to accelerate understanding of the data: Combining transfer learning and active learning, we present an annotation tool that selects and annotates the most informative samples one at a time. To annotate multiple samples simultaneously, we present a tool that allows annotation in the embedding space of a variational autoencoder manipulated by a classification head. For both approaches, we provide no-code web applications for intuitive use by domain experts.