Abstract: Methods and arrangements for facilitating data clustering. From a set of input data, a predetermined number of non-overlapping subsets are created. The input data is split recursively to create the subsets.

Abstract: A method, in accordance with the present invention, which may be implemented by a program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform steps for providing emotions for a conversational system, includes representing each of a plurality of emotions as an entity. A level of each emotion is updated responsive either user stimuli or internal stimuli or both. When a threshold level is achieved for each emotion, the user stimuli and internal stimuli are reacted to by notifying components subscribing to each emotion to take appropriate action.

Abstract: Methods and arrangements for facilitating speaker identification. At least one N-best list is generated based on input speech, a system output is posited based on the input speech, and a determination is made, via at least one property of the N-best list, as to whether the posited system output is inconclusive.

Abstract: A system and method for verifying user identity, in accordance with the present invention, includes a conversational system for receiving inputs from a user and transforming the inputs into formal commands. A behavior verifier is coupled to the conversational system for extracting features from the inputs. The features include behavior patterns of the user. The behavior verifier is adapted to compare the input behavior to a behavior model to determine if the user is authorized to interact with the system.

Abstract: A system and method of the present invention for determining and maintaining dialog focus in a conversational speech system includes presenting a command associated with an application to a dialog manager. The application associated with the command is unknown to the dialog manager at the time it is made. The dialog manager determines a current context of the command by reviewing a multi-modal history of events. At least one method is determined responsive to the command based on the current context. The at least one method is executed responsive to the command associated with the application.

Abstract: A system and method for intelligent caching and network management includes contextual information representing needs of a user. A contextual system determines settings based on the contextual information and determines services and devices available for the user, in accordance with the contextual information. A predictor receives the contextual information, the settings, the services available and the devices available and predicts the needs of the user to make resources available to the user in accordance with predictions.

Abstract: A system and method for verifying user identity, in accordance with the present invention, includes a conversational system for receiving inputs from a user and transforming the inputs into formal commands. A behavior verifier is coupled to the conversational system for extracting features from the inputs. The features include behavior patterns of the user. The behavior verifier is adapted to compare the input behavior to a behavior model to determine if the user is authorized to interact with the system.

Abstract: An apparatus for automatically identifying command boundaries in a conversational natural language system, in accordance with the present invention, includes a speech recognizer for converting an input signal to recognized text and a boundary identifier coupled to the speech recognizer for receiving the recognized text and determining if a command is present in the recognized text, the boundary identifier outputting the command if present in the recognized text. A method for identifying command boundaries in a conversational natural language system is also included.

Abstract: In accordance with the invention, a method and system for accessing a dialog system employing a plurality of different clients, includes providing a first client device for accessing a conversational system and presenting a command to the conversational system by converting the command to a form understandable to the conversational system. The command is interpreted by employing a mediator, a dialog manager and a multi-modal history to determine the intent of the command based on a context of the command. A second client device is determined based on a predetermined device preference stored in the conversational system. An application is abstracted to perform the command, and the results of the performance of the command are set to the second client device.

Abstract: An apparatus for automatically identifying command boundaries in a conversational natural language system, in accordance with the present invention, includes a speech recognizer for converting an input signal to recognized text and a boundary identifier coupled to the speech recognizer for receiving the recognized text and determining if a command is present in the recognized text, the boundary identifier outputting the command if present in the recognized text. A method for identifying command boundaries in a conversational natural language system is also included.

Abstract: A method for hierarchical translation of input to a formal command in natural language understanding systems includes presenting an input command to be translated to a natural language understanding engine. At least two translator levels are provided in the natural language understanding engine. A first translator level of the at least two translator levels translates the input command into at least one category by associating the input command with the at least one category for the next level of translators. A formal language command is output for the input command from a last of the at least two translator levels based on the input command and the at least one category.

Abstract: Disclosed is a method and apparatus for building a domain-specific language model for use in language processing applications, e.g., speech recognition. A reference language model is generated based on a relatively small seed corpus containing linguistic units relevant to the domain. An external corpus containing a large number of linguistic units is accessed. Using the reference language model, linguistic units which have a sufficient degree of relevance to the domain are extracted from the external corpus. The reference language model is then updated based on the seed corpus and the extracted linguistic units. The process may be repeated iteratively until the language model is of satisfactory quality. The language building technique may be further enhanced by combining it with mixture modeling or class-based modeling.