Mercurial > hg > dcase2013_sc_rnh
changeset 2:def2b3fa1450 tip master
corrected README
| author | Gerard Roma <gerard.roma@upf.edu> |
|---|---|
| date | Mon, 04 Nov 2013 10:46:05 +0000 |
| parents | 96b1b8697b60 |
| children | |
| files | README.md |
| diffstat | 1 files changed, 6 insertions(+), 4 deletions(-) [+] |
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--- a/README.md Mon Nov 04 10:43:51 2013 +0000 +++ b/README.md Mon Nov 04 10:46:05 2013 +0000 @@ -1,9 +1,11 @@ -The files in this folder represent our submission for the Scene Classificatoin task of the IEEE D-CASE AASP Challenge (http://c4dm.eecs.qmul.ac.uk/sceneseventschallenge/) +The files in this repository represent our submission for the Scene Classificatoin task of the IEEE D-CASE AASP Challenge (http://c4dm.eecs.qmul.ac.uk/sceneseventschallenge/) -The code has been tested mainly on Matlab2012 on OSX +The code has been tested mainly on Matlab2012 on OSX. + Required libraries: rastamat and libsvm The implemented approach is described in: + G. Roma, W. Nogueira, P.Herrera, _Recurrence Quantification Analysis Features for Environmental Sound Recognition_. Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. New Paltz, USA 2013. The main files are: @@ -12,12 +14,12 @@ * analyze_files.m * RQA.m -The rest of matlab files can be used to test the code. Some of the files are taken from: https://soundsoftware.ac.uk/projects/aasp-d-case-metrics +The rest of matlab files can be used to test the code. Some of the files are taken from https://soundsoftware.ac.uk/projects/aasp-d-case-metrics Two submissions were sent to the challenge, one uses hardcoded SVM parameters, the other does grid search: classify_scenes(tmp_path, train_file,test_file, output_file, 0) % use hardcoded parameters for SVM classify_scenes(tmp_path, train_file,test_file, output_file, 1) % use grid search -The temp_path is used to store features. +temp_path is used to store features.