Detection and Classification of Acoustic Scenes and Events (DCASE) challenge: Large-scale weakly labeled semi-supervised sound event detection in domestic environments
Sprache des Titels:
Englisch
Original Kurzfassung:
The task evaluates systems for the large-scale detection of sound events using weakly labeled data (without timestamps). The target of the systems is to provide not only the event class but also the event time boundaries given that multiple events can be present in an audio recording. Another challenge of the task is to explore the possibility to exploit a large amount of unbalanced and unlabeled training data together with a small weakly annotated training set to improve system performance. The labels in the annotated subset are verified and can be considered as reliable. The data are Youtube video excerpts from domestic context which have many applications such as ambient assisted living. The domain was chosen due to the scientific challenges (wide variety of sounds, time-localized events...) and potential industrial applications.
Forschungs-