Method for detecting a signal pause between two patterns which are present on a time-variant measurement signal using hidden Markov models

Abstract

The method recognizes a signal pause between two patterns that are present in a time-variant measurement signal and that are recognized using hidden Markov models. In a first signal processing stage, feature vectors are formed periodically for pattern recognition, which describe a signal curve of a measurement signal within a time slice. No speech pause is detected by a pause detector contained therein in a first time slice based on present features of a first feature vector. In a second signal processing stage, in a second time slice that follows the first time slice the first feature vector is compared with at least two hidden Markov models, of which at least one has been trained to a pattern to be recognized and another has been trained to a pattern characteristic for a pause. If in the comparison of the first feature vector with the hidden Markov models, a greater probability results for the presence of a pause, pause information concerning the presence of a pause, the pause information, is forwarded to a pause detector in the first signal processing stage. The measurement signal is treated as a signal pause, at least in the second time slice.

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