English(EN) An Analysis of Untrained Deep Reservoir Networks for Audio Surveillance

未训练深度水库网络在音频监控方面展现出潜力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-20 20:39

研究人员探索了用于音频监控的未训练深度水库网络，特别是双向回声状态网络。在MIVIA音频事件数据集上，针对不同噪声水平下的紧急声音事件检测对这些模型进行了评估。研究发现，更深的水库网络在嘈杂条件下表现更好，而更浅的网络效率更高，适合NVIDIA Orin等边缘设备。该方法在对数梅尔频谱图和MFCCs等不同输入表示下均表现出鲁棒性。 AI

影响未训练的水库架构为资源受限环境下的音频监控提供了一种有前景且高效的解决方案。

排序理由该集群包含一篇学术论文，详细介绍了对用于音频监控的深度水库网络的新分析。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Patrizio Dazzi · 2026-06-20 20:39

Untrained Deep Reservoir Networks for Audio Surveillance Analysis

In this paper, we investigate untrained recurrent models from the Reservoir Computing (RC) paradigm for audio surveillance, focusing on bidirectional Echo State Networks with different depths, from shallow to deep configurations, for emergency sound event detection. We evaluate t…

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Untrained Deep Reservoir Networks for Audio Surveillance Analysis

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