Abstract: A system and method for classifying a voice signal to one of a set of predefined categories, based upon a statistical analysis of features extracted from the voice signal. The system includes an acoustic processor and a classifier. The acoustic processor extracts features that are characteristic of the voice signal and generates feature vectors using the extracted spectral features. The classifier uses the feature vectors to compute the probability that the voice signal belongs to each of the predefined categories and classifies the voice signal to a predefined category that is associated with the highest probability.

Abstract: A system and method for classifying a voice signal to one of a set of predefined categories, based upon a statistical analysis of features extracted from the voice signal. The system includes an acoustic processor and a classifier. The acoustic processor extracts features that are characteristic of the voice signal and generates feature vectors using the extracted spectral features. The classifier uses the feature vectors to compute the probability that the voice signal belongs to each of the predefined categories and classifies the voice signal to a predefined category that is associated with the highest probability.

Abstract: A system and method for electronic communication management comprises a universal data model, a modeling engine, and an adaptive knowledge base. The modeling engine includes a natural language processor and a statistical modeler. A communication is translated from its native format into the universal data model. The modeling engine determines the intent of the communication using the natural language processor and the statistical modeler. A response is generated, either automatically or by an agent. An audit module analyzes each response and provides feedback to the modeling engine and the adaptive knowledge base. The modeling engine uses the feedback to update models in the adaptive knowledge base. The modeling engine supports various application specific modules.

Abstract: A system and method for electronic communication management comprises a universal data model, a modeling engine, and an adaptive knowledge base. The modeling engine includes a natural language processor and a statistical modeler. A communication is translated from its native format into the universal data model. The modeling engine determines the intent of the communication using the natural language processor and the statistical modeler. A response is generated, either automatically or by an agent. An audit module analyzes each response and provides feedback to the modeling engine and the adaptive knowledge base. The modeling engine uses the feedback to update models in the adaptive knowledge base. The modeling engine supports various application specific modules.