Speech recognition system, training arrangement and method of calculating iteration values for free parameters of a maximum-entropy speech model
First Claim
1. A method of calculating iteration values for free parameters λ
-
α
ortho(n) of a maximum-entropy speech model MESM in a speech recognition system with the aid of the generalized iterative scaling training algorithm, the method comprising the step ofiteratively determining;
λ
α
ortho(n+1)=G(λ
α
ortho(n), mα
ortho, . . . )
where;
n;
is an iteration parameter;
G;
is a mathematical function;
α
;
is an attribute in the MESM; and
mα
ortho;
is a desired orthogonalized boundary value in the MESM for the attribute α
,characterized in that the desired orthogonalized boundary value mα
ortho is calculated by linearly combining the desired boundary value mα
with desired boundary values mβ
of attributes β
that have a larger range than the attribute α
.
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Abstract
The invention relates to a speech recognition system and a method of calculating iteration values for free parameters λαortho(n) of a maximum-entropy speech model MESM with the aid of the generalized-iterative scaling training algorithm in a computer-supported speech recognition system in accordance with the formula λαortho(n+1)=G(λαortho(n), mαortho, . . . ), where n is an iteration parameter, G a mathematical function, α an attribute in the MESM and mαortho a desired orthogonalized boundary value in the MESM for the attribute α. It is an object of the invention to further develop the system and method so that they make a fast computation of the free parameters λ possible without a change of the original training object. According to the invention this object is achieved in that the desired orthogonalized boundary value mαortho is calculated by a linear combination of the desired boundary value mα with desired boundary values mβ from attributes β that have a larger range than the attribute α. mα and mβ are then desired boundary values of the original training object.
49 Citations
15 Claims
-
1. A method of calculating iteration values for free parameters λ
-
α
ortho(n) of a maximum-entropy speech model MESM in a speech recognition system with the aid of the generalized iterative scaling training algorithm, the method comprising the step ofiteratively determining;
λ
α
ortho(n+1)=G(λ
α
ortho(n), mα
ortho, . . . )
where;n;
is an iteration parameter;G;
is a mathematical function;α
;
is an attribute in the MESM; andmα
ortho;
is a desired orthogonalized boundary value in the MESM for the attribute α
,characterized in that the desired orthogonalized boundary value mα
ortho is calculated by linearly combining the desired boundary value mα
with desired boundary values mβ
of attributes β
that have a larger range than the attribute α
. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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α
Specification