CRNNs for 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 https://github.com/multitel-ai/urban-sound-tagging.

4 pages, 5 figures, DCASE2020 Challenge - DCASE

References in corpus (3)

• Large Batch Training of Convolutional Networks
• Time2Vec: Learning a Vector Representation of Time
• SONYC-UST-V2: An Urban Sound Tagging Dataset with Spatiotemporal Context