Data-driven design of RASTA-like filters

Abstract

We describe use of Linear Discriminant Analysis LDA for data-driven automatic design of RASTA-like lters.The LDA applied to rather long segments of time trajectories of critical-band energies yields FIR lters to be applied to these time trajectories in the feature extraction module.Frequency responses of the rst three discriminant v ectors are in principle consistent with the ad hoc designed RASTA, delta and double-delta lters.On a connected digit task the new features outperform the original RASTA processing.