Semi-automatic classification of bird vocalizations using spectral peak tracks
Semi-automatic classification of bird vocalizations using spectral peak tracks
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DOI：
10.1121/1.2345831
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发表时间：
2006-11-01
影响因子：
2.4
通讯作者：
Maher, Robert C.
中科院分区：
文献类型：
--
作者：
Chen, Zhixin;Maher, Robert C.
鸟类叫声的离线自动分类和识别一直是鸟类学家和模式检测研究人员感兴趣的课题。一些新的应用，包括飞机避免鸟撞的鸟叫声分类，将需要在噪声和其他干扰的存在下进行真实的时间分类。许多常见鸟类的发声可以使用正弦曲线和模型来表示。利用计算机软件对谱分析数据进行峰值跟踪的实验表明，正弦曲线和模型对孤立鸟类音节的快速自动识别是有用的。该技术通过对记录的鸟类发声进行时变分析来导出一组光谱特征，然后计算导出的参数与从一组参考鸟类发声确定的一组存储的模板相匹配的程度。这种相对简单的技术的结果对于干净和有噪声的记录都是有利的。(c)2006年，美国声学学会。
Automatic off-line classification and recognition of bird vocalizations has been a subject of interest to ornithologists and pattern detection researchers for many years. Several new applications, including bird vocalization classification for aircraft bird strike avoidance, will require real time classification in the presence of noise and other disturbances. The vocalizations of many common bird species can be represented using a sum-of-sinusoids model. An experiment using computer software to perform peak tracking of spectral analysis data demonstrates the usefulness of the sum-of-sinusoids model for rapid automatic recognition of isolated bird syllables. The technique derives a set of spectral features by time-variant analysis of the recorded bird vocalizations, then performs a calculation of the degree to which the derived parameters match a set of stored templates that were determined from a set of reference bird vocalizations. The results of this relatively simple technique are favorable for both clean and noisy recordings. (c) 2006 Acoustical Society of America.