SDLGASAug 24, 2020

CRNNs for Urban Sound Tagging with spatiotemporal context

arXiv:2008.10413v214 citationsHas Code
AI Analysis

This is an incremental application of existing methods to a specific domain problem for audio researchers.

The paper tackled urban sound tagging with spatiotemporal context using CRNNs for the DCASE 2020 challenge, achieving competitive results as part of a benchmark task.

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.

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