A voice dialog device includes a sight line detection unit configured to detect a sight line of a user, a voice acquiring unit configured to acquire voice pronounced by the user, and a processor. The processor is configured to perform a step of acquiring a result of recognizing the voice, a step of determining whether or not the user is driving, and a step of determining whether or not the voice dialog device has a dialog with the user. When the detected sight line of the user is in a certain direction, and a start keyword has been detected from the voice, the processor determines that the user has started a dialog. The processor switches the certain direction based on whether the user is driving.

Voice dialog device and voice dialog method

Systems and methods are provided for receiving and processing a query to determine an intent of the query, and analyzing the intent of the query to determine that the intent of the query is associated with a use case state diagram. Systems and methods further provide for traversing a plurality of nodes in the user case state diagram to generate a value for each relevant node, performing an operation associated with the query using the generated values, and providing the results of the operation to a computing device.

Dialog system for transitioning between state diagrams

An adaptable interface for retrieving available electronic digital assistant services is provided. A user interface including a graphical underlay on which user input gestures may be operated is displayed via a display element. A particular user input gesture selecting a sub-portion of the graphical underlay is detected. The selected sub-portion of the graphical underlay, or metadata associated therewith, is provided to an electronic digital assistant services query identification function. Identities of one or more available electronic digital assistant services that may be performed on objects or information included in the selected sub-portion of the graphical underlay or metadata associated therewith are received. And one or more actionable user interface elements are displayed on, over, or adjacent to the graphical underlay corresponding to the received identities of the one or more available electronic digital assistant services.

Adaptable interface for retrieving available electronic digital assistant services

Systems and methods are disclosed for extending application functionality via conversational interfaces. In one implementation, a first communication is received from an interaction engine. The first communication is processed to identify an application that the communication is directed to, The first communication is provided to an application extension engine associated with the first application. A second communication is received from the application extension engine. The second communication is provided to the interaction engine.

Extending application functionality via conversational interfaces

A method, computer system, and computer program product digitally manipulate a human resources workflow on a mobile device. A selection of a human resources operation is received from a mobile application executing on the mobile device; a business rule corresponding to the human resources operation is identified. The business rule comprises a plurality of linked metadata objects forming a syntax tree. The plurality of linked metadata objects is interpreted to implement the business rule, Interpreting comprises sending a first set of chat messages that request input for the plurality of linked metadata objects, and receiving a second set of chat messages that provide the requested input. The human resources operation is performed according to the business rule, generating a workflow stage notification, and publishing the workflow stage notification to a set of mobile devices for display on a timeline of the mobile application.

Metadata-based chat wizard

Systems and methods are provided for digital assistant configuration and functionality. For example, systems and methods provide for receiving a query from a user via a computing device, processing language in the query to identify a plurality of elements associated with the query, and analyzing the plurality of elements associated with the query to determine an intent of the query by mapping the plurality of elements associated with the query to a list of predetermined intents by comparing the plurality of elements associated with the query to each intent in the list of predetermined intents to generate a score for each intent in the list of predetermined intents. Systems and methods further provide for determining a subset of the predetermined intents based on the score for each intent in the list of predetermined intents, and providing recommendations related to the query based on the subset of predetermined intents.

Digital assistant query intent recommendation generation

In an example, for each one or more search terms, pieces of data from flat data are searched to locate one or more matching pieces of data from the flat data, wherein a piece of data from the flat data matches if it contains at least one attribute with a value that is similar to the search term. Then, for each matching piece of data from the flat data, a fuzzy match score and a match frequency score are calculated. For each node in a graph structure, a ranking score based on a combination of the fuzzy match score and the match frequency score for a corresponding piece of data from the flat data is calculated. One or more search results are retrurned based on the ranking scores of nodes corresponding to pieces of data for the one or more search results.

Internet of things search and discovery dynamic alteration of results

In an example, one or more tokens in a freeform search query are identified, each token corresponding to a search term or combination of neighboring search terms in the freeform search query. A graph structure and flat data corresponding to the graph structure are obtained. A search for results relevant to the identified one or more tokens is performed using a first search process, the first search process using the graph structure and flat data to rank search results according to a first ranking order and populate a why found table. Pieces of data corresponding to the results relevant to the identified one or more tokens are joined using the why found table, forming a view and one or more patterns of operators and terms, in a pattern database, matching the one or more operators and one or more surrounding terms in the freeform search query are found.

Internet of things structured query language query formation

In an example, data in a non-flat format and metadata corresponding to the data are obtained from a first database. The data is flattened into flat data and augmented with the metadata. One or more pieces of the flat data are scanned to locate a first piece of flat data having a first attribute with attribute values that are a subset of attribute values of a second attribute of a second piece of flat data. A link is then created between the first attribute of the first piece of flat data and the second attribute of the second piece of flat data. A graph structure is generated, the graph structure containing a plurality of nodes, each node corresponding to a data type of the flat data and corresponding to one or more pieces of data in the flat data of the corresponding data type.

Haichao Wei

Papers

Digital assistant query intent recommendation generation

Dialog system for transitioning between state diagrams

Internet of things search and discovery dynamic alteration of results

Internet of things structured query language query formation

Internet of things search and discovery graph engine construction