Appeal No. 1996-2198
Application 08/077,506
frame models can be derived from samples of speech.
. . .
. . . .
It is noted that Kuroda does not explicitly
teach the use of "probability density." However, it
would have been obvious to one of ordinary skill in
the art to use probability density functions with
the Hidden Markov models of Kuroda because Baker
teaches that it is well known in the art to develop
probability density functions from the analysis
parameters used in Markov models (figure 2). [Paper
No. 31, at 7.]
We do not agree. As already noted, the parameter values
generated by Kuroda's training and adaptation blocks 8 and 9
and stored in parameter table 11 represent discrete
probability values rather than a continuous probability
function. Turning now to Baker, Figure 2 shows each frame 62
of a spoken sequence 60 having twelve spectral parameters 64,
whose energy levels are depicted in bar graph 65 (col. 12,
lines 29-42). After the frames are grouped by the operator4
into segments 66A-E representing different speech sounds (col.
13, lines 3-19), all of the frames of a segment are combined
to form a phonetic frame model 70 having a different
4The actual embodiment tested by the inventor,
twenty-four spectral parameters were used (col. 12, lines 42-
45).
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