自动环境声音识别的神经网络

Svetlana Segarceanu, G. Suciu, I. Gavat
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引用次数: 2

摘要

环境声音识别是当前计算机科学与机器人、安全或环境保护领域的一个重要而有价值的领域。基础方法从主要的语音应用特征方法发展到更具体的方法,随着深度学习范式的出现,出现了许多使用这些方法的尝试。本文通过对前馈神经网络的几种结构的探索,重新开启了我们对前馈神经网络应用的研究,并在我们的研究中引入了卷积神经网络。实验考虑了三类森林特有的声音,旨在检测电锯声、车辆声和真正的森林声。
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Neural Networks for Automatic Environmental Sound Recognition
Environmental sound recognition is currently an important and valuable field of computer science and robotics, security or environmental protection. The underlying methodology evolved from primary speech application characteristic methods to more specific approaches, and with the advent of the deep learning paradigm many attempts using these methods arose. The paper reopens the research we have started on the application of the Feed Forward Neural Networks, by exploring several configurations, and introduces the Convolutional Neural Networks in our investigation. The experiments consider three classes of forest specific sounds and meant to detect the chainsaw sounds, vehicle, and genuine forest.
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