Abstract: A method of linking data is disclosed. The method comprises receiving and analyzing an anchor word and determining one or more related words to the anchor word using one or more data sources. Further, the method comprises displaying the anchor word and the one or more related words in a graphical user interface (GUI) in a display, wherein the one or more related words are clustered around the anchor word.

Abstract: An apparatus for training an image classification model according to an embodiment disclosed includes a first trainer that trains a model body and a first head through supervised learning based on a labeled data set subjected to type 1 labeling, a second trainer that trains the model body, the first head, and a second head through multi-task learning based on the labeled data set and an unlabeled data set, and a third trainer that trains a plurality of third heads through supervised learning based on the labeled data set subjected to type 2 labeling while freezing the model body.

Abstract: An inspection apparatus includes: a hardware processor that: conducts an inspection on an image by comparing a scanned image with a correct image, the image being formed on paper in accordance with a print job, the scanned image being generated by reading the image, the correct image serving as a reference for the inspection of the image; and determines whether a page is a target for the inspection in accordance with a type of the paper on which the image will be formed according to print setting of the print job, wherein the hardware processor conducts the inspection on the image on a page that has been determined to be the target for the inspection by the hardware processor, and does not conduct the inspection on the image on a page that has been determined to not be the target for the inspection.

Abstract: System and method for determining an outcome probability of an event based on videos are disclosed. The method includes receiving the videos of an event, creating a building block model, extracting one of an audio content, a video content from the videos, analysing extracted content, generating an analysis result, analysing an engagement between speaker and participant of event, generating a data lake comprising a keyword library, computing the outcome probability of the event, enabling the building block model to learn from the data lake and the outcome probability computed and representing the at least one outcome probability in a pre-defined format.

Abstract: Systems, methods, and computer-readable storage media for quantifying meeting effectiveness for an individual. A system configured as disclosed herein uses data from multiple meetings in which a user participated to create a user profile for the user. The system then receives data related to a new meeting in which the user participated, processes the new meeting data into segments using natural language processing, tags the resulting segments based on contexts, and compares the tagged segments to the user profile to generate a meeting effectiveness score for the new meeting which is specific to the user. The system can use machine learning to iteratively improve an ability of the system to generate the tagged segments using historical meeting data and updating that historical meeting data with each iteration of scoring a meeting's effectiveness.

Abstract: A communication system comprising an information processing apparatus and a mobile terminal, wherein when the mobile terminal receives a packet transmitted from the information processing apparatus, it determines whether or not a login condition for transmitting a login request is satisfied based on a received signal strength of the packet, and it transmits the login request to the information processing apparatus in a case where it determines that the login condition is satisfied, and does not transmit the login request to the information processing apparatus in a case where it is determines that the login condition is not satisfied.

Abstract: A state of a user operation performed on a mobile terminal is registered in a Web server that can be accessed from the mobile terminal and a multifunction peripheral (MFP) in association with information about the user, and the state of the user operation is handed over to the MFP based on the registered information by the user simply logging into the MFP.

Abstract: Common events between layers on a semiconductor wafer are filtered. Common events should contain the majority of defects of interest. Only nuisance events that are common between layers on the semiconductor wafer remain, which reduces the nuisance rate. Defects that are common across layers can be filtered based on, for example, defect coordinates, a difference image, or defect attributes.

Abstract: A method for providing a user interface (UI) for generating training data for an artificial intelligence (AI) model may include providing, for display via the UI, image information that depicts an object, a set of operations of the object, and a process associated with the set of operations. The method may include providing, for display via the UI, text information that describes the object, the set of operations of the object, and the process associated with the set of operations. The method may include receiving, via the UI, a user input that associates respective image information of the image information with corresponding text information of the text information. The method may include generating association information that associates the respective image information with the corresponding text information, based on the user input. The method may include generating discourse and semantic information from the text information associated to the image information.

Abstract: Access authentication in an artificial intelligence system includes perceiving electronically with a first user's artificial intelligence voice response system (AIVRS) a physical presence of a second user. A voice request is generated by the first user's AIVRS and conveyed to a second user requesting access to a knowledge corpus stored by an AIVRS of the second user. Based on a voice response of the second user, the first user's AIVRS instantiates an electronic communications session with the second user's AIVRS. The session is initiated via an electronic communications connection with a portable device of the second user. Selected portions of the knowledge corpus are retrieved by the first user's AIVRS from the second user's AIVRS, the portions selected based on the voice response. An action by one or more IoT devices is initiated in response to a voice prompt interpreted by the first user's AIVRS based on the selected portions.

Abstract: Techniques include a method of providing a user interface on a device. The user interface has at least a first display portion, a second display portion and a third display portion, the second display portion including a link to the third display portion that, when activated by a user, cause the device to present the third display portion of the user interface, the first display portion not including the link to the third display portion. The method includes causing the first display portion to be displayed. The method further includes receiving audible input while the first display portion is being displayed. The method further includes determining that the third display portion corresponds to an utterance in the audible input based at least in part on labels determined to match the utterance. The method further includes causing the third display portion to be displayed.

Abstract: Transferring (e.g., automatically) an automated assistant routine between client devices during execution of the automated assistant routine. The automated assistant routine can correspond to a set of actions to be performed by one or more agents and/or one or more devices. While content, corresponding to an action of the routine, is being rendered at a particular device, the user may walk away from the particular device and toward a separate device. The automated assistant routine can be automatically transferred in response, and the separate device can continue to rendering the content for the user.

Abstract: An image processing system includes an image processing device configured to process an image, a microphone configured to acquire sound, a display configured to display information, and one or more controllers. The one or more controllers are configured to function as a unit configured to acquire text information based on voice information acquired via the microphone, and a unit configured to cause the image processing device to execute image processing in response to an execution command being acquired from the text information, and to cause the display to display, in response to an execution command related to the image processing being not acquired from the text information and a setting command related to the image processing being acquired, a screen for waiting for an execution instruction to execute image processing that is based on at least the setting command.

Abstract: A method provides for assistance in recognition of an entity. A set of data and associated information corresponding to a plurality of entities known to an assisted user is received, such that an instance of the set of data and associated information includes identification of a respective entity of the plurality of entities known to an assisted user. Real-time data corresponding to a first entity is received from one or more devices capturing the real-time data. The real-time data is compared to the set of data and associated information corresponding to the plurality of entities known to the user to determine whether the first entity has a known relevance to the user, and in response to determining the first entity does have a known relevance to the user, the processor provides the identity and relevance of the first entity to the user.

Abstract: A method, computer system, and a computer program product for task monitoring is provided. The present invention may include training an AI voice response system based on task performance data, wherein the task performance data originates from at least one monitoring device. The present invention may include receiving a request for instructions to complete a task from a user. The present invention may include monitoring a performance of the task by the user, wherein the performance of the task by the user is monitored utilizing at least one monitoring device. The present invention may include determining differences between the performance of the task by the user and a task sequence.

Abstract: This disclosure involves executing artificial intelligence models that infer image editing operations from natural language requests spoken by a user. Further, this disclosure performs the inferred image editing operations using inferred parameters for the image editing operations. Systems and methods may be provided that infer one or more image editing operations from a natural language request associated with a source image, locate areas of the source that are relevant to the one or more image editing operations to generate image masks, and performing the one or more image editing operations to generate a modified source image.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for processing data. According to exemplary implementations of the present disclosure, a method for processing data includes: determining a factor associated with a first input of a deep learning model, wherein the factor affects the number of threads for executing the deep learning model; generating a plurality of first partial inputs by using the first input based on the factor, wherein each first partial input in the plurality of first partial inputs is a part of the first input; and performing an operation on the plurality of first partial inputs by using the deep learning model, and generating an output of the deep learning model. Thereby, the data processing performance can be improved, and the resource requirement for data processing is lowered.

Abstract: An exemplary supporting audio element for a furniture item may include a control circuit positioned within a body portion, a supporting leg, and a loudspeaker. The supporting audio element may be mounted to a furniture item, for supporting the furniture item, and configured for one or more of, without limitation, communicating with an external audio device, playing audio, controlling a function of the furniture item, voice recognition, and voice control. An exemplary supporting audio element may include a microphone connected to a phonetic recognition module, for receiving and recognizing voice commands and relaying the voice commands to the control circuit for controlling a function of the supporting audio leg and the furniture item. A furniture item may include an exemplary supporting audio element for incorporating the features thereof.

Abstract: Identifying documents that contain potential code words using a machine learning model. In some embodiments, a method may include receiving documents, identifying a first corpus and a second corpus in the documents, extracting a first set of word embeddings from the first corpus and a second set of word embeddings from the second corpus, generating a first vector space for the first set of word embeddings and a second vector space for the second set of word embeddings using a machine learning model, performing a vector rotation to improve alignment of the first set of word embeddings with the second set of word embeddings, identifying a word embedding in the first vector space that is not aligned with a corresponding word embedding in the second vector space as a potential code word, and identifying one or more documents that contain the potential code word in the first corpus.

Abstract: This application provides a voice interaction processing method and apparatus, to achieve a friendly and natural voice interaction effect and reduce power consumption. In the method, a microprocessor enables an image collector only when determining, based on voice data collected by a voice collector, that a first user is a target user; then the image collector collects user image data and transmits the user image data to the microprocessor; and the microprocessor sends a wakeup instruction to an application processor only when determining, based on the user image data, that the target user is in a voice interaction state. Based on the foregoing method, nus-enabling of the image collector and the application processor is avoided to some extent, and power consumption is reduced.