Abstract

A speech recognition method and apparatus for recognizing word strings in a continuous audio signal are disclosed. The word strings are made up of a plurality of elements, and each element, generally a word, is represented by an element template defined by a plurality of target patterns. Each target pattern is represented by a plurality of statistics describing the expected behavior of a group of spectra selected from plural short-term spectra generated by processing of the incoming audio. Each target pattern has associated therewith at least one required dwell time position and at least one optional dwell time position. The number of required dwell time positions and the sum of the required and optional dwell time positions define, in effect, the limits of a time interval during which a given target pattern can be said to match an incoming sequence of frame patterns. The incoming audio spectra are processed to enhance the separation between the spectral pattern classes during later analysis. The processed audio spectra are grouped into multi-frame spectral patterns and are compared, using likelihood statistics, with the target patterns of the element templates. Each multi-frame pattern input, which inputs occur at a frame rate which requires each keyword target pattern to correspond to at least two of the multi-frame patterns, is forced to contribute to each of a plurality of pattern scores as represented by the element templates. The contributions of said multi-frame pattern inputs to said pattern scores is controlled, in part, by said required and optional dwell time constraints. A concatenation technique is employed, using dynamic programming techniques, to determine the correct identity of the word string.

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