Recognizing Bird Species in Audio Recordings using Deep Convolutional Neural Networks
Recognizing Bird Species in Audio Recordings using Deep Convolutional Neural Networks
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发表时间：
2016
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通讯作者：
Karol J. Piczak
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作者：
Karol J. Piczak
． 本文总结了一种基于卷积神经网络的纯音频鸟类物种识别方法。该方法是在LifeCLEF 2016鸟类识别任务的背景下进行评估的，该任务是在包含34128个音频记录的数据集上进行的公开挑战，这些录音记录代表了来自南美洲的999种鸟类。该任务考虑了三种不同的网络架构和一个简单的集成模型，集成提交的平均精度为41.2%（官方分数）和52.9%（前景物种）。
. This paper summarizes a method for purely audio-based bird species recognition through the application of convolutional neural networks. The approach is evaluated in the context of the LifeCLEF 2016 bird identification task - an open challenge conducted on a dataset containing 34 128 audio recordings representing 999 bird species from South America. Three different network architectures and a simple ensemble model are considered for this task, with the ensemble submission achieving a mean average precision of 41.2% (official score) and 52.9% for foreground species.