An approach to scoring acoustically-based events, such as hypothesized instances of keywords, in a speech processing system make use of scores of individual components of the event. Data characterizing an instance of an event are first accepted. This data includes a score for the event. The event is associated with a number of component events from a set of component events, such as a set of phonemes. Probability models are also accepted for component scores associated with each of the set of component events in each of two of more possible classes of the event, such as a class of true occurrences of the event and a class of false detections of the event. The event is then scored. This scoring includes computing a probability of one of the two or more possible classes for the event using the accepted probability models.
Word spotting score normalization