Modelling overlapping sound events: a multi-label or multi-class problem? - Huy Phan
2021 Intelligent Sensing Winter School
Modelling overlapping sound events: a multi-label or multi-class problem?
Huy Phan, Queen Mary University of London
Polyphonic sound events are the main error source of audio event detection (AED) systems. This work investigates to frame the task as a multi-class classification problem by considering each possible label combination as one class. To circumvent the large number of arising classes due to combinatorial explosion, the event categories are decomposed into multiple groups to form a multi-task problem in a divide-and-conquer fashion, where each of the tasks is a multi-class classification problem. A network architecture is then devised for multi-task modelling. Experiments on a database with high degree of event overlap show that the proposed approach results in more favorable performance than the widely used multi-label approach.
Slides: http://cis.eecs.qmul.ac.uk/2021Winter...
As part of the 2021 Intelligent Sensing Winter School: http://cis.eecs.qmul.ac.uk/school2021...