Notice of RetractionSpeech recognition based on a compound kernel support vector machine

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

To improve the learning and generalization ability of the machine-learning model, a new compound kernel that may pay attention to the similar degree between sample space and feature space is proposed. In this paper, used the new compound kernel support vector machine to a speech recognition system for Chinese isolated words, non-specific person and middle glossary quantity, and compared the speech recognition results with the SVM using traditional kernels and with using RBF network. Experiments showed that the SVM performance with the new compound kernel is much better than with traditional kernels and has higher correct recognition rates than ones of using RBF network in different SNRs, and is of shorter training time.