Markov Modelling in Iso La Ted Word Recognition
نویسنده
چکیده
This paper presents a speaker independent isolated word recogniser, which combines the product codebook vector quantisation principle with the discrete hidden Markov modeHing (HMM), so that each frame in the unknown test word ( or training word) is described by two symbols, the linear predictive coding (LPC) shape and gain. The recogniser (both training and testing) has been evaluated on a 12 word vocabulary. The recognition results as well as the implementation requirements are discussed and compared with other approaches to speaker independent isolated word recognition.
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تاریخ انتشار 2006