Appeal No. 2000-0189 Page 2
Application No. 08/864,460
vectors to a label series of clusters to which they belong. A
continuous distribution probability density HMM generating
means generates a continuous distribution probability density
HMM from a quantized vector series corresponding to each label
of the label series. Incidence of a label in each state is
calculated from the training vectors classified in the same
clusters and the continuous distribution probability density
HMM.
Claim 1, which is representative for present purposes,
follows:
1. An HMM (Hidden Markov Model) generator,
comprising:
vector quantizing means for generating a model
by quantizing vectors of a training pattern having a
vector series, and converting said quantizing
vectors into a label series of clusters to which
they belong,
continuous probability distribution density HMM
generating means for generating a continuous
probability distribution density HMM from a
quantized vector series corresponding to each label
of said label series of clusters, and
label incidence calculating means for
calculating the incidence of the labels in each
state from said quantizing vectors of a training
pattern classified in the same label series of
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Last modified: November 3, 2007