Abstract: A telephone-based interactive speech recognition system is retrained using variable weighting and incremental retraining. Variable weighting involves changing the relative influence of particular measurement data to be reflected in a statistical model. Statistical model data is determined based upon an initial set of measurement data determined from an initial set of speech utterances. When new statistical model data is to be generated to reflect new measurement data determined from new speech utterances, a weighting factor is applied to the new measurement data to generate weighted new measurement data. The new statistical model data is then determined based upon the initial set of measurement data and the weighted new measurement data. Incremental retraining involves generating new statistical model data using prior statistical model data to reduce the amount of prior measurement data that must be maintained and processed.

Abstract: A method and apparatus are provided for improving the performance of an interactive speech application. The interactive speech application is developed and deployed for use by one or more callers. During execution, the interactive speech application stores, in a log, event information that describes each task carried out by the interactive speech application in response to interaction with the one or more callers. The application also stores one or more sets of audio information, in which each of the sets of audio information is associated with one or more utterances by one of the callers. Each of the sets of audio information is associated with one of the tasks represented in the log. After the log is established, an analytical report is displayed. The report describes selective actions taken by the interactive speech application while executing, and selective actions taken by one or more callers while interacting with the interactive speech application.