Robust SBR method for adverse Mandarin speech recognition - Electronics Letters
نویسنده
چکیده
10 RRSBR An RNN-based robust signal bias removal (RRSBR) method is proposed for improving both the recognition performance and the computational efficiency of the SBR method for adverse Mandarin speech recognition. It differs from the SBR method in using three broadclass sub-codebooks to encode the feature vector of each frame and combining the three encoding residuals to form the frame-level signal bias estimate. A novel approach involving softly combining the board-class encoding residuals using dynamic weighting functions generated by an RNN is applied. Experimental results show that the RRSBR method significantly outperforms the SBR method.
منابع مشابه
On-line Mandarin Phonetic Symbol Recognition for Video-based Fingertip Input System, " Revised in Journal of Visual Communication and Image Representation
[1] Wei-Tyng Hong, “Hidden Conditional Random Fields for Resource-constrained Speech Recognition”, Advanced Science Letters. (accepted, 2011) (EI, SCI) [2] Wei-Tyng Hong, “An Investigation on Robust Confidence Measure and Model Compensations for Smartphone-based Speech Recognition”, International Journal of Advanced Information Technologies. (accepted, 2011) [3] Wei-Tyng Hong, “Text-independent...
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