Speech recognition in noisy environment using weighted projection-based likelihood measure
نویسندگان
چکیده
This paper investigates a projection-based likelihood meaure that improves speech recognition performance in noisy environment. The projection-based likelihood measure is modi ed to give the weighting and projection e ect and to reduce computational complexity. It is evaluated in sub-model based word recognition using semi-continuous hidden Markov model with speaker independent mode. Experimental results using proposed measure are reported for several performance factors: additive noise and noisy channel environment, various noise signals, and combination with other compensation method. In various noisy environments, performance improvements were achieved compared to the previously existing methods.
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