gerard@2: 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/)
gerard@1: 
gerard@2: The code has been tested mainly on Matlab2012 on OSX.
gerard@2: 
gerard@1: Required libraries: rastamat and libsvm
gerard@1: 
gerard@1: The implemented approach is described in:
gerard@2: 
gerard@1: 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.
gerard@1: 
gerard@1: The main files are:
gerard@1: 
gerard@1: * classify_scenes.m
gerard@1: * analyze_files.m
gerard@1: * RQA.m
gerard@1: 
gerard@2: 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
gerard@1: 
gerard@1: Two submissions were sent to the challenge, one uses hardcoded SVM parameters, the other does grid search:
gerard@1: 
gerard@1: classify_scenes(tmp_path, train_file,test_file, output_file, 0) % use hardcoded parameters for SVM  
gerard@1: classify_scenes(tmp_path, train_file,test_file, output_file, 1) % use grid search 
gerard@1: 
gerard@2: temp_path is used to store features.
gerard@1: