Appeal 2007-1864
Application 10/100,717
Simultaneously, the spectral data segments are also applied to
multiple class matrix multipliers 72 that provide vectorial outputs
representative of predetermined articulatory parameter values. The class
distinction vector information (i.e., obtained from the normalized probability
class vector 68) is directed to plural multipliers 70 for combination with the
output of the class matrix multipliers 72. As a result, a weighed average of
class vectors is generated for a given sound. These resultant class vectors
are then combined to form a single feature vector 76 whose elements are the
articulatory parameter values for the speech data being processed (Hutchins,
col. 3, l. 68 - col. 4, l. 11; col. 4, ll. 37-49; col. 17, ll. 7-38; Fig. 6).
Turning now to the rejection, we note at the outset that the Examiner
indicates that the “predicted value” limitation in claim 1 corresponds to
Hutchins’ predefined articulatory parameters (Answer 6-7). The Examiner,
however, also indicates that the “articulatory dynamics value at a previous
time” likewise corresponds to the “predefined acoustic or articulatory
parameter (Answer 6). While we generally agree with the Examiner that a
predefined parameter corresponds to a parameter defined earlier in time, we
fail to see how these predefined parameters themselves can reasonably
correspond to both to the predicted value limitation and previous
articulatory dynamics values. These predefined parameters characterizing
the relevant anatomical aspects of interest,6 however, are used as the basis
for the single feature vector 76. This vector results from the mapping
process -- a mapping process which accounts for the probability that the
speech has certain spectral characteristics.
6 See n.4, supra, of this opinion.
6
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