Abstract: A human-machine dialogue system is described which has multiple computer-implemented dialogue components. A user client delivers output prompts to a human user and receives dialogue inputs from the human user including speech inputs. An automatic speech recognition (ASR) engine processes the speech inputs to determine corresponding sequences of representative text words. A natural language understanding (NLU) engine processes the text words to determine corresponding NLU-ranked semantic interpretations. A semantic re-ranking module re-ranks the NLU-ranked semantic interpretations based on at least one of dialogue context information and world knowledge information. A dialogue manager responds to the re-ranked semantic interpretations and generates the output prompts so as to manage a dialogue process with the human user.

Abstract: Current human-to-machine interfaces enable users to interact with a company's database and enter into a series of transactions (e.g., purchasing products/services and paying bills). Each transaction may require several operations or stages requiring user input or interaction. Some systems enable a user to enter a voice input parameter providing multiple operations of instruction (e.g., single natural language command). However, users of such a system do not know what types of commands the system is capable of accepting. Embodiments of the present invention facilitate communications for user transactions by determining a user's goal transaction and presenting a visual representation of a voice input parameter for the goal transaction. The use of visual representations notifies the user of the system's capability of accepting single natural language commands and the types of commands the system is capable of accepting, thereby enabling a user to complete a transaction in a shorter period of time.