Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10429198 | Tsinghua Science & Technology | 2005 | 9 Pages |
Abstract
This work describes an improved feature extractor algorithm to extract the peripheral features of point x(ti,fj) using a nonlinear algorithm to compute the nonlinear time spectrum (NL-TS) pattern. The algorithm observes nÃn neighborhoods of the point in all directions, and then incorporates the peripheral features using the Mel frequency cepstrum components (MFCCs)-based feature extractor of the Tsinghua electronic engineering speech processing (THEESP) for Mandarin automatic speech recognition (MASR) system as replacements of the dynamic features with different feature combinations. In this algorithm, the orthogonal bases are extracted directly from the speech data using discrite cosime transformation (DCT) with 3Ã3 blocks on an NL-TS pattern as the peripheral features. The new primal bases are then selected and simplified in the form of the Îdp-t operator in the time direction and the Îdp-f operator in the frequency direction. The algorithm has 23.29% improvements of the relative error rate in comparison with the standard MFCC feature-set and the dynamic features in tests using THEESP with the duration distribution-based hidden Markov model (DDBHMM) based on MASR system.
Related Topics
Physical Sciences and Engineering
Engineering
Engineering (General)
Authors
Al-dulaimy Fadhil H.T., Wang (çä½è±),