Abstract: An example device includes a user interface component that implements a user interface and receives a visualization request value from user operations; an inspection database comprising an aggregation of inspection data; and a controller, comprising: a facility planning circuit that interprets a user facility visualization value in response to the visualization request value; a facility inspection data circuit that interprets the aggregation of inspection data in response to the user facility visualization value; a geographic depiction circuit that determines a geographic display boundary and a hierarchical inspection presentation for at least one industrial facility positioned within the geographic display boundary in response to the user facility visualization value and the aggregation of inspection data, and determines a user geographic display value in response to the geographic display boundary and the hierarchical inspection presentation.

Abstract: Methods and systems are provided for creating a calendar event using context. A natural language expression including at least one of words, terms, and phrases of text may be received at a calendar event creation module from an application. The calendar event creation module may identify one or more slots in the text of the natural language expression related to the calendar event using a first grammar module and a second grammar module. The one or more slots identified by the first grammar module and the second grammar module that indicate a calendar event may be compared to determine whether there is a match between the one or more identified slots. If a match is found, at least one calendar event using the one or more slots identified by the first grammar module and the second grammar module may be created.

Abstract: Aspects of the present disclosure relate to systems and methods for identifying and providing a passage that is highly convincing in terms of one or more stances for a given topic. A convincingness ranking model is based on a machine learning model, a multi-layer feed forward neural network with a back propagation for updating for example. The query represents a stance under a topic. A convincingness ranking model trainer identifies passage pairs that relate to the query, and labels the passage pairs according to relative levels of convincingness from the stance between the two passages in the respective passage pairs. The trainer provides a user interface to interactively receive selections of the relative levels of convincingness of the passage pairs. The system ranks passages from the passage pairs based on the labels and filter out specific passages when the rank forms a cyclic relationship in a directed graph.

Abstract: Methods and systems are provided for creating a calendar event using context. A natural language expression including at least one of words, terms, and phrases of text may be received at a calendar event creation module from an application. The calendar event creation module may identify one or more slots in the text of the natural language expression related to the calendar event using a first grammar module and a second grammar module. The one or more slots identified by the first grammar module and the second grammar module that indicate a calendar event may be compared to determine whether there is a match between the one or more identified slots. If a match is found, at least one calendar event using the one or more slots identified by the first grammar module and the second grammar module may be created.

Abstract: Methods and systems are provided for creating a calendar event using context. A natural language expression including at least one of words, terms, and phrases of text may be received at a calendar event creation module from an application. The calendar event creation module may identify one or more slots in the text of the natural language expression related to the calendar event using a first grammar module and a second grammar module. The one or more slots identified by the first grammar module and the second grammar module that indicate a calendar event may be compared to determine whether there is a match between the one or more identified slots. If a match is found, at least one calendar event using the one or more slots identified by the first grammar module and the second grammar module may be created.

Abstract: Methods and systems are provided for creating a calendar event using context. A natural language expression including at least one of words, terms, and phrases of text may be received at a calendar event creation module from an application. The calendar event creation module may identify one or more slots in the text of the natural language expression related to the calendar event using a first grammar module and a second grammar module. The one or more slots identified by the first grammar module and the second grammar module that indicate a calendar event may be compared to determine whether there is a match between the one or more identified slots. If a match is found, at least one calendar event using the one or more slots identified by the first grammar module and the second grammar module may be created.

Abstract: A speech data retrieval apparatus (10) includes a speech database (1), a speech recognition unit (2), a confusion network creation unit (3), an inverted index table creation unit (4), a query input unit (6), a query conversion unit (7) and a label string check unit (8). The speech recognition unit (2) reads speech data from the speech database (1), carries out a speech recognition process with respect to the read speech data, and outputs a result of speech recognition process as a lattice in which a phoneme, a syllable, or a word is a base unit. The confusion network creation unit (3) creates a confusion network based on the output lattice and outputs the result of speech recognition process as the confusion network. The inverted index table creation unit (4) creates an inverted index table based on the output confusion network.

Abstract: A speech data retrieval apparatus (10) includes a speech database (1), a speech recognition unit (2), a confusion network creation unit (3), an inverted index table creation unit (4), a query input unit (6), a query conversion unit (7) and a label string check unit (8). The speech recognition unit (2) reads speech data from the speech database (1), carries out a speech recognition process with respect to the read speech data, and outputs a result of speech recognition process as a lattice in which a phoneme, a syllable, or a word is a base unit. The confusion network creation unit (3) creates a confusion network based on the output lattice and outputs the result of speech recognition process as the confusion network. The inverted index table creation unit (4) creates an inverted index table based on the output confusion network.