Communication Dans Un Congrès Année : 2024

Performance and Energy Balance: A Comprehensive Study of State-of-the-Art Sound Event Detection Systems

Résumé

In recent years, deep learning systems have shown a concerning trend toward increased complexity and higher energy consumption. As researchers in this domain and organizers of one of the Detection and Classification of Acoustic Scenes and Events challenges task, we recognize the importance of addressing the environmental impact of data-driven SED systems. In this paper, we propose an analysis focused on SED systems based on the challenge submissions. This includes a comparison across the past two years and a detailed analysis of this year's SED systems. Through this research, we aim to explore how the SED systems are evolving every year in relation to their energy efficiency implications 1 .

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hal-04892368 , version 1 (16-01-2025)

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Francesca Ronchini, Romain Serizel. Performance and Energy Balance: A Comprehensive Study of State-of-the-Art Sound Event Detection Systems. ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2024, Seoul, South Korea. pp.1096-1100, ⟨10.1109/ICASSP48485.2024.10445834⟩. ⟨hal-04892368⟩
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