Speech recognition system, training arrangement and method of calculating iteration values for free parameters of a maximum-entropy speech model

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.

Dependencies are inferred from the claim text.