Abstract: A method and system is presented for providing information to a user interactively using a conversation manager thereby mimicking a live personal assistant. Communication between the user and the system can be implemented orally and/or by using visual cues or other images. The conversation manager relies on a set of functions defining very flexible adaptive scripts. As a session with a user is progressing, the conversation manager, obtains information from the user refining or defining more accurately what information is required by the user. Responses from the user result in the selection of different scripts or subscripts. In the process of obtaining information, data may be collected that is available either locally, from a local sensor, or remotely from other sources. The remote sources are accessed by automatically activating an appropriate function such as a search engine and performing a search over the Internet.

Abstract: A simplification of the process of developing call or dialog flows for use in an Interactive Voice Response system is provided. Three principal aspects of the invention include a task-oriented dialog model (or task model), development tool and a Dialog Manager. The task model is a framework for describing the application-specific information needed to perform the task. The development tool is an object that interprets a user specified task model and outputs information for a spoken dialog system to perform according to the specified task model. The Dialog Manager is a runtime system that uses output from the development tool in carrying out interactive dialogs to perform the task specified according to the task model. The Dialog Manager conducts the dialog using the task model and its built-in knowledge of dialog management. Thus, generic knowledge of how to conduct a dialog is separated from the specific information to be collected in a particular application.

Abstract: Apparatus and method are provided for segmenting, parsing, interpreting and formatting the content of instructions such as air traffic control instructions. Output from a speech recognizer is so processed to produce such instructions in a structured format such as for input to other software. There are two main components: an instruction segmenter and a robust parser. In the instruction segmenter, the recognized text produced by the speech recognizer is segmented into independent instructions and each instruction is processed. The instruction segmenter receives a recognized air traffic control or other instruction, and segments it into individual commands. Utterances or other language are thereby broken up into their component instructions by detecting probable instruction boundaries. If normal processing fails, then robust backup processing is invoked, as a fallback after a fixed time per word has elapsed or a processing failure has occurred.