A system and a method to correct semantic interpretation recognition errors presented in this invention applies to Automatic Speech Recognition systems returning recognition results with semantic interpretations. The method finds the most likely intended semantic interpretation given the recognized sequence of words and the recognized semantic interpretation. The key point is the computation of the conditional probability of the recognized sequence of words given the recognized semantic interpretation and a particular intended semantic interpretation. It is done with the use of Conditional Language Models which are Statistical Language Models trained on a corpus of utterances collected under the condition of a particular recognized semantic interpretation and a particular intended semantic interpretation. Based on these conditional probabilities and the joint probabilities of the recognized and intended semantic interpretations, new semantic interpretation confidences are computed. The semantic interpretation with the maximum new confidence is declared the corrected semantic interpretation.
Method and system for post-processing speech recognition results