Modified DCTNet for audio signals classification

Yin Xian, Yunchen Pu, Zhe Gan, Liang Lu, Andrew Thompson

Research output: Contribution to journalJournal articlepeer-review


We introduced the use of modified DCTNet for audio signals feature extraction. The modified DCTNet is a development of DCTNet, with its center frequencies of filterbanks geometrically spaced. The modified DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to human audio perception. We use features extracted by the modified DCTNet and put them to classifiers. Experimental results on bird song classification, music genre classification, and artist identification show that the modified DCTNet and RNN improve classification rate, and achieve state of the art performance.
Original languageEnglish
Article number3405
JournalJournal of the Acoustical Society of America
Issue number4
Publication statusPublished - 1 Oct 2016


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