Apparatus and method for normalizing and categorizing linear prediction code vectors using Bayesian categorization technique

A pattern matching system provided for performing a sequence of single syllables recognition comprising:

• a receiver for receiving an incoming syllable utterance of either a standard syllable or a single unknown syllable for syllable recognition in the form of wavefunctions;
• an analog to digital conversion means for converting said wavefunctions to a plurality of digital data representing said wave functions;
• a linear predictive coding (LPC) means for converting said digital data representing said input wavefunction into a LPC cepstra vector;
• a compression means for compressing said each LPC cepstra vector into a compressed cepstra vector wherein said unknown syllable is represented by a set of categorizing vectors X where X={x(1),x(2),x(3), . . . ,x(k)};
• a dictionary means for storing a plurality of standard compressed cepstra vectors each representing a standard single syllable by a set of feature vectors C(1), C(2), C(3), . . . , and C(M);
• a Bayesian-decision-rule categorizing means for computing a conditional normal density function .function.(x.vertline. Ci) for each of said feature vectors Ci, assuming that said function .function.(x.vertline. Ci) having a normal distribution and said x(1), x(2), x(3), . . . and x(k) are stochastically independent;,
• said Bayesian-decision-rule categorizing means further employing functional parameters of said normal distribution for said normal density function .function.(x.vertline. Ci) to apply a Bayesian decision rule to deterministically identify said single unknown syllable with one of said standard syllables;
• and
• an user interface means to low an user of said pattern matching system to provide input data and commands for controlling the operation of said matching system.

A method for matching and categorizing an input pattern of waveform applicable for syllable recognition comprising the steps of:.

• (a) storing in a dictionary means a plurality of standard patterns wherein each of said standard patterns representing a standard single syllable by a set of feature vectors C(1), C(2), C(3), . . . , and C(M) and M being a positive integer;
• (b) converting said input pattern of waveform representing an unknown single syllable into a categorizing pattern for representing said unknown syllable by a set of categorizing vectors X where X={x(1), x(2), x(3), . . . ,x(k)} and k being a positive integer;
• (c) utilizing a Bayesian-decision-rule categorizing means for computing a conditional normal density function .function.(x.vertline. Ci) wherein said function .function.(x.vertline. Ci) having a normal distribution and said x(1), x(2), x(3), . . . and x(k) are stochastically independent;, and
• (d) employing functional parameters of said normal distribution for said normal density function .function.(x.vertline. Ci) to apply a Bayesian decision rule to identify said input unknown single syllable with one of said standard single syllables.