Non-sequential automatic classification of anuran sounds for the estimation of climate-change indicators

作者：

Highlights：

• A non-sequential method for classifying sounds is proposed.

• The procedure relies on featuring frame sounds using MPEG-7 parameters.

• Several machine learning classifiers are compared and the decision tree is selected.

• It has been applied to classify anuran sounds as an indicator of global warming.

摘要

•A non-sequential method for classifying sounds is proposed.•The procedure relies on featuring frame sounds using MPEG-7 parameters.•Several machine learning classifiers are compared and the decision tree is selected.•It has been applied to classify anuran sounds as an indicator of global warming.

论文关键词：Global warming,Sound classification,Machine learning,Data mining,Feature extraction

论文评审过程：Received 1 December 2016, Revised 27 September 2017, Accepted 9 November 2017, Available online 10 November 2017, Version of Record 24 November 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.11.016