Hierarchical Pooling Structure for Weakly Labeled Sound Event Detection
This work addresses sound event detection for audio processing applications, but it is incremental as it builds on existing pooling methods without introducing new parameters.
The paper tackled the problem of sound event detection with weakly labeled data by proposing a hierarchical pooling structure, which improved performance on three pooling functions without adding parameters and achieved competitive results on the DCASE 2017 Challenge Task 4.
Sound event detection with weakly labeled data is considered as a problem of multi-instance learning. And the choice of pooling function is the key to solving this problem. In this paper, we proposed a hierarchical pooling structure to improve the performance of weakly labeled sound event detection system. Proposed pooling structure has made remarkable improvements on three types of pooling function without adding any parameters. Moreover, our system has achieved competitive performance on Task 4 of Detection and Classification of Acoustic Scenes and Events (DCASE) 2017 Challenge using hierarchical pooling structure.