Data-driven design of RASTA-like filters
نویسندگان
چکیده
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 vectors 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.
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