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)(2023)
摘要
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 tasks, 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.
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关键词
sound event detection,machine listening,energy consumption,carbon footprint
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