DCTNet and ADCTNet

This file contains MATLAB codes that generate audio DCTNet feature. This work has been shown in the paper: Adaptive DCTNet for Audio Signal Classification, and PCANet and DCTNet for Acoustic Signals Feature Extraction.

It has been published by the Journal of Acoustical Society of America and the International Conference of Acoustic and Speech Signal Processing (ICASSP) 2017.

About the codes:

1. "bird_song_example" folder contains 4 bird song wav file, ADCTNet and DCTNet feature code.

"ADCTNet_demo.m" is a MATLAB demo file to generate bird song ADCTNet feature.

2. "handel_example" folder contains codes to generate 2-layer ADCTNet and DCTNet feature for Handel's "Messiah" in MATLAB.

"ADCTNet_music_demo.m" is a MATLAB demo file to generate music ADCTNet feature,

"dctnet_music_demo.m" is a file to generate music dctnet feature. "stdct.m" is the short time DCT function.

3. "plot_in_paper" folder contains MATLAB codes to generate ADCTNet, DCTNet, MFSC, LFSC, ERB-rate and scattering transform feature, and a data .mat file.

"ADCTNet_paper_demo.m" is a MATLAB demo file to generate music ADCTNet feature,

"dctnet_demo.m" is a file to generate music dctnet feature. "stdct.m" is the short time DCT function.

"comparison2_feature.m" generates features for comparison: MFSC, LFSC, ERB-rate and scattering transform.

This folder can generate figures appeared in papers: "Adaptive DCTNet for Audio Signal Classification" (https://arxiv.org/abs/1612.04028), "DCTNet and PCANet for Acoustic Signal Feature Extraction" (https://arxiv.org/abs/1605.01755).

To generate MFSC, LFSC, ERB-rate features for comparison, we need voicebox MATLAB toolbox (http://www.ee.ic.ac.uk/hp/staff/dmb/voicebox/voicebox.html).

To generate scattering transform feature, we need scatnet MATLAB toolbox (http://www.di.ens.fr/data/software/scatnet/quickstart-audio/).