Romain Serizel, Nicolas Turpault, Hamid Eghbal-Zadeh, Ankit Parag Shah,
"Large-scale weakly labeled semi-supervised sound event detection in domestic environments"
: Proceedings of Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), 2018
Original Titel:
Large-scale weakly labeled semi-supervised sound event detection in domestic environments
Sprache des Titels:
Englisch
Original Buchtitel:
Proceedings of Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE)
Original Kurzfassung:
This paper presents DCASE 2018 task 4. The task evaluates systems
for the large-scale detection of sound events using weakly labeled
data (without time boundaries). 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 labeled training set to improve system performance.
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.