mlsanityData to 14 Oct 2026

CRNNs for Urban Sound Tagging with spatiotemporal context

arXiv 2008.10413 ↗First posted 24 Aug 2020cs.SD cs.LG eess.AScited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Aug 2020.

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Citing papers per year: 2022: 1; 2023: 1.

2 papers.

  1. 2022Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMFcited by 23
  2. 2023Tackling Interpretability in Audio Classification Networks with Non-negative Matrix Factorizationcited by 5