Abstract: Methods, apparatuses, and systems are presented for generating natural language models using a novel system architecture for feature extraction. A method for extracting features for natural language processing comprises: accessing one or more tokens generated from a document to be processed; receiving one or more feature types defined by user; receiving selection of one or more feature types from a plurality of system-defined and user-defined feature types, wherein each feature type comprises one or more rules for generating features; receiving one or more parameters for the selected feature types, wherein the one or more rules for generating features are defined at least in part by the parameters; generating features associated with the document to be processed based on the selected feature types and the received parameters; and outputting the generated features in a format common among all feature types.

Abstract: An automated, scalable call-taking system integrates with existing telephony infrastructures and enables, through use of speech recognition, DTMF detection, text-to-speech (TTS), and other related software or hardware, the inputting, access, and retrieval of information to and from multiple back-end dispatch and booking systems without the need for a human operator.