2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

Technical Program

Paper Detail

Paper IDAUD-13.4
Paper Title THE BENEFIT OF TEMPORALLY-STRONG LABELS IN AUDIO EVENT CLASSIFICATION
Authors Shawn Hershey, Daniel P. W. Ellis, Eduardo Fonseca, Aren Jansen, Caroline Liu, R Channing Moore, Manoj Plakal, Google, United States
SessionAUD-13: Detection and Classification of Acoustic Scenes and Events 2: Weak supervision
LocationGather.Town
Session Time:Wednesday, 09 June, 15:30 - 16:15
Presentation Time:Wednesday, 09 June, 15:30 - 16:15
Presentation Poster
Topic Audio and Acoustic Signal Processing: [AUD-CLAS] Detection and Classification of Acoustic Scenes and Events
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Virtual Presentation  Click here to watch in the Virtual Conference
Abstract To reveal the importance of temporal precision in ground truth audio event labels, we collected precise (∼0.1 sec resolution) “strong” labels for a portion of the AudioSet dataset. We devised a temporallystrong evaluation set (including explicit negatives of varying difficulty) and a small strong-labeled training subset of 67k clips (compared to the original dataset’s 1.8M clips labeled at 10 sec resolution). We show that fine-tuning with a mix of weak- and stronglylabeled data can substantially improve classifier performance, even when evaluated using only the original weak labels. For a ResNet50 architecture, d' on the strong evaluation data including explicit negatives improves from 1.13 to 1.41. The new labels are available as an update to AudioSet.