1. In a computing device having a first expert and a second expert that recognize user input, a method of determining a parameter to tune the second expert relative to the first expert so that a mathematical combination of recognition results from the first and second experts increases overall recognition accuracy, comprising: a) selecting a tuning sample from a set, each sample comprising input data and a label indicating an intended meaning of the input data; b) applying the tuning sample to the first expert to obtain a first matching set of scores corresponding to prototypes that match the label and a first non-matching set of scores corresponding to prototypes that do not match the label; c) applying the tuning sample to the second expert to obtain a second matching set of scores corresponding to prototypes that match the label and a second non-matching set of scores corresponding to prototypes that do not match the label; d) comparing at least some of the matching scores in the first matching set to at least some of the non-matching scores in the first non-matching set, and at least some of the matching scores in the second matching set to at least some of the non-matching scores in the second non-matching set, to determine at least one range of parameter values that when applied to the second expert do not change a correct result of the first expert to an incorrect one or improve recognition by correcting an incorrect result of the first expert; e) recording range data about each range in a data structure; f) repeating b) through e) for a plurality of other samples, whereby the data structure includes data about a plurality of ranges; and g) analyzing the range data in the data structure to determine a parameter value that provides better recognition accuracy when the second expert is tuned therewith than when tuned with other parameter values.