Bioacoustic signal classification in continuous recordings: Syllable-segmentation vs sliding-window

作者：

Highlights：

• Propose an end-to-end approach for frog call classification based 1D CNN-LSTM.

• Compare syllable-segmentation and sliding-window based frog call classification.

• Develop an adaptive threshold decision method for syllable segmentation .

摘要

•Propose an end-to-end approach for frog call classification based 1D CNN-LSTM.•Compare syllable-segmentation and sliding-window based frog call classification.•Develop an adaptive threshold decision method for syllable segmentation .

论文关键词：Bioacoustic signal classification,Bioacoustic signal segmentation,1D convolutional neural network

论文评审过程：Received 12 June 2019, Revised 13 March 2020, Accepted 15 March 2020, Available online 16 March 2020, Version of Record 21 March 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113390