Robust interpretation of speech

In all fields of pattern recognition there may arise situations where severe distortions of the sensor data or errors of processing prevent a successful analysis. This is especially true in speech recognition. Therefore, a speech understanding system can not rely on being able to interpret the whole or even a given fixed percentage of the input data. Rather a dynamic criterion has to be applied to decide when the analysis has produced the best results obtainable from the input data. We propose an appropriate criterion and show how the requirements for robust interpretation of speech can be met in a dialog system.