CRNNs for Urban Sound Tagging with spatiotemporal context
Published in
arXiv.org(2020)External Links:
TL
TL;DR
This paper describes CRNNs the authors used to participate in Task 5 of the DCASE 2020 challenge, which focuses on hierarchical multilabel urban sound tagging with spatiotemporal context.
Abstract
This paper describes CRNNs we used to participate in Task 5 of the DCASE 2020 challenge. This task focuses on hierarchical multilabel urban sound tagging with spatiotemporal context. The code is available on our GitHub repository at this https URL.
References21 items
1
SONYC-UST-V2: An Urban Sound Tagging Dataset with Spatiotemporal Context
2
PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition
3
Sound Event Detection of Weakly Labelled Data With CNN-Transformer and Automatic Threshold Optimization
4
On the Variance of the Adaptive Learning Rate and Beyond
5