BIOACOUSTICAL SPECIES CLASSIFICATION BASED ON SYLLABIC MEL CEPSTRUM FEATURES AND K-NEAREST NEIGHBORS CLASSIFIER

机译：基于Syllabic Mel谱特征的生物声学物种分类和K最近邻居分类器

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Amphibian decline and trends in bird population sizes are cases of major environmental concerns in biology, in view of the fact that the presence of amphibians and birds are good indicators of the health of an ecosystem. As a consequence, efficient methods for monitoring and identifying the presence of species are an imperative. In this work, a conceptual framework for bioacoustical species classification is formulated and an instantiation of this framework is presented in the form a sensor array processing (SAP) system. A developing application capability, based on Mel-frequency cepstrum coefficients (MFCC), principal components analysis (PCA), and k-nearest neighbors (k-NN) that allows identifying species from their audio vocalizations is discussed.

机译：两栖动物下降和鸟类人口尺寸的趋势是生物学的主要环境问题的案例，鉴于两栖动物和鸟类的存在是生态系统健康的良好指标。因此，监测和识别物种存在的有效方法是一个势在必行的。在这项工作中，配制了生物声学种类分类的概念框架，并且该框架的实例化以传感器阵列处理（SAP）系统的形式呈现。讨论了基于熔体频率谱系数（MFCC），主成分分析（PCA）和允许从其音频发声识别物种的K-COMPORY分析（K-NN）的主要应用能力。

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《International Conference on Artificial Intelligence and Pattern Recognition》|2010年||共7页
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Gonzalo Vaca-Castano; Domingo Rodriguez;
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中图分类 TP18-53;
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Bioacoustical identification; Mel-frequency cepstrum coefficients(MFCC); Principal component analy-sis(PCA); K-nearest neighbor(k-NN);

机译：生物声学识别;熔融频率综合系数（MFCC）;主成分分析 - SIS（PCA）;K-最近邻（K-NN）;

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BIOACOUSTICAL SPECIES CLASSIFICATION BASED ON SYLLABIC MEL CEPSTRUM FEATURES AND K-NEAREST NEIGHBORS CLASSIFIER

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