Speech recognition system utilizing pre-calculated similarity measurements

摘要

An input utterance is converted to a sequence of standard or prototype data frames which are compared with word models which are represented by respective sequences of standard or prototype probability states, there being a pre-calculable distance metric representing the degree of match between each prototype data frame and each prototype model state. Only distance measurements better than a calculated threshold are considered meaningful and those meaningful metrics are stored in a packed list. Also stored is an address array of offsets for locating particular meaningful metrics in the list, the address array being accessed by the corresponding frame and state indices. Also stored is an array for distinguishing meaningful and non-meaningful metrics. Accordingly, an input utterance can be evaluated by locating meaningful metrics in the packed list using the address array and by utilizing a default value for any non-meaningful metric.