Multi-resolution RASTA filtering for TANDEM-based ASR

New speech representation based on multiple filtering of temporal trajectories of speech energies in frequency sub-bands is proposed and tested. The technique extends earlier works on delta features and RASTA filtering by processing temporal trajectories by a bank of band-pass filters with varying resolutions. In initial tests on OGI Digits database the technique yields about 30% relative improvement in word error rate over the conventional PLP features. Since the applied filters have zero-mean impulse responses, the technique is inherently robust to linear distortions.

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