Annotating sound events through interactive design of interpretable features – #7726
Professionals of all domains of expertise expect to take part in the benefits of the machine learning (ML) revolution, but realisation is often slowed down by lack of familiarity with ML concepts and tools, as well as low availability of annotated data for supervised methods. Inspired by the problem of assessing the impact of human-generated activity on marine ecosystems through passive acoustic monitoring [1], we are developing Seadash, an interactive tool for event detection and classification in multivariate time series.