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- W2363919242 abstract "In order to improve the lloise robustness of speech recognition system based on continuous Hidden MarkovModels(CHMM), Mel-frequency cepstrum coefficient of relative auto-corre1ation sequence (RAS_MFCC+ △ RAS_MFCC) isproposed to suppress additive stationary and convolution noise in the feature space. This method can be used to enhance thesystem robustness effectively as to improve the recognition rate in the low signal-to-noise ratio environment. We also adopt amethod called hybrid speech training of CHMM where the trained CHMM parameters have better adaptive ability to theenvironment with various signal-to-noise ratios. Experiments show that this method combining with noise suppression infeature space and compensation at system mode1 level can greatly improve system'S recognition performance in noisecontaminated environments." @default.
- W2363919242 created "2016-06-24" @default.
- W2363919242 creator A5051145717 @default.
- W2363919242 date "1999-01-01" @default.
- W2363919242 modified "2023-09-23" @default.
- W2363919242 title "A Robust Recognition Method of Isolated Words Based On Continuous HMM" @default.
- W2363919242 hasPublicationYear "1999" @default.
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