Signal bias removal with orthogonal transform for adverse Mandarin speech recognition

Wern J. Wang, Sin-Horng Chen

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

A new method for applying orthogonal transforms in signal bias removal (SBR) for adverse Mandarin speech recognition (MSR) is proposed. The orthogonal transform process is performed in a moving window manner to extract features from the input speech. Codewords are then obtained by matching high-order, bias-free features with pre-trained codebooks for bias estimation. The effectiveness of the method has been confirmed by an experiment involving multi-speaker adverse continuous MSR. Significant improvements in the recognition accuracy and computation time were achieved as compared with the conventional SBR method.

Original languageEnglish
Pages (from-to)851-852
Number of pages2
JournalElectronics Letters
Volume36
Issue number9
DOIs
StatePublished - 27 Apr 2000

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