In this paper we present an improved Sequential Forward Floating Search algorithm. Subsequently, extensive tests are carried out on a selection of French emotional language resources well suited for a first impression on general applicability. A detailed analysis is presented to test the various modifications suggested one-by-one. Our conclusion is that the modification in the forward step result in a considerable improvement in speed (~80%) while no considerable and systematic loss in quality is experienced. The modifications in the backward step seem to have only significance when a higher number of features is achieved. The final clarification of this issue remains the task of future work. As a result we may suggest a quick feature selection algorithm, which is practically more suitable for the state of the art, larger corpora and wider feature-banks. Our quick SFFS is general: it can also be used in any other field of application.
Bibliographic reference. Brendel, Mátyás / Zaccarelli, Riccardo / Devillers, Laurence (2010): "A quick sequential forward floating feature selection algorithm for emotion detection from speech", In INTERSPEECH-2010, 1157-1160.