Abstract: Conversation user interfaces that are configured for virtual assistant interaction may include contextual interface items that are based on contextual information. The contextual information may relate to a current or previous conversation between a user and a virtual assistant and/or may relate to other types of information, such as a location of a user, an orientation of a device, missing information, and so on. The conversation user interfaces may additionally, or alternatively, control an input mode based on contextual information, such as an inferred input mode of a user or a location of a user. Further, the conversation user interfaces may tag conversation items by saving the conversation items to a tray and/or associating the conversation items with indicators.

Abstract: The present application includes a method and system for multi-channel interaction. A communication session is initiated between a customer service representative (CSR) and an end user. Multi-channel communication is used between the end user and the CSR. The multi-channel communication includes at least voice and data. Information is presented to the end user via a user interface, and the user can confirm the accuracy of the information using the user interface.

Abstract: The present invention is a method and system for automatedly producing at least one desktop analytics trigger. Upon receiving at least one type of data input, the system analyzes the data input and produces at least one desktop analytics trigger based on the results of the analysis of the data input. The data input can include data on the programs, applications, or information a user utilizes during a task, to allow use of desktop process analytics. This process may be used to either generate a new desktop analytics trigger or update an existing desktop analytics trigger.

Abstract: A method of workforce optimization includes acquiring video data. The video data is obtained from a plurality of video cameras in a facility comprising a plurality of departments. A customer load for each of the plurality of departments is identified. A location of each of a plurality of employees in the facility is identified. A customer-to-employee ratio is determined for each department. The determined customer-to-employee ratio for each department is provided to a computing device. At least one employee deployment notification is provided from the computing device to another computing device.

Abstract: The present invention is a system and method for projective channel hopping within a customer engagement center (CEC) system. The CEC system receives a customer through a system entry point and receives, from the customer, a communication in a current customer service representative (CSR) channel in the CEC system. The CEC system assesses its ability to connect the customer with a CSR on the current CSR channel using a smart routing engine (SRE), which also assesses its current ability to connect the customer with a CSR on other equivalent CSR channels. Using the SRE, the CEC system compares its ability to connect the customer with a CSR on current and equivalent CSR channels to determine if the customer should remain on their current CSR channel or transfer to a new one. In the latter case, the CEC system offers the customer a chance to change channels or remain on their current channel.

Abstract: A method of determining influence of language elements in script to an overall classification of the script includes performing a sentiment analysis of the language elements. In some instances, for example, in a conversation, the language elements and turns within the conversation (e.g., in a chat bot) are analyzed for their influence in escalation or non-escalation of the conversation to a higher level of resolution, e.g., to a human representative or manager.

Abstract: A system and method for searching a video stream collected by a camera in a video surveillance system for an object's placement or displacement is disclosed. The searching includes an interactive question/answer approach that allows for a video snippet including the object's placement or displacement to be found quickly without the need for complicated video analytics. During the search, frames from algorithmically selected points in the video stream are presented to a user for review. The user reviews each frame and indicates if he/she sees the object. Based on the user's response the searching algorithmically reduces the portion video stream that is searched until a snippet of a video is found that includes the object's placement or displacement.

Abstract: The present invention is a system and method of continuous sentiment tracking and the determination of optimized agent actions through the training of sentiment models and applying the sentiment models to new incoming interactions. The system receives conversations comprising incoming interactions and agent actions and determines customer sentiment on a micro-interaction level for each incoming interaction. Based on interaction types, the system correlates the determined sentiment with the agent action received prior to the sentiment determination to create and train sentiment models. Sentiment models include agent action recommendations for a desired sentiment outcome. Once trained, the sentiment models can be applied to new incoming interactions to provide CSRs with actions that will yield a desired sentiment outcome.

Abstract: Attention weights in a hierarchical attention network indicate the relative importance of portions of a conversation between an individual at one terminal and a computer or a human agent at another terminal. Weighting the portions of the conversation after converting the conversation to a standard text format allows for a computer to graphically highlight, by color, font, or other indicator visible on a graphical user interface, which portions of a conversation led to an escalation of the interaction from an intelligent virtual assistant to a human customer service agent.

Abstract: The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.

Abstract: A conversation user interface enables a patient to better understand their healthcare by integrating diagnosis, treatment, medication management, and/or payment, through a system that uses a virtual assistant to engage in conversation with the patient. The conversation user interface conveys a visual representation of a conversation between the virtual assistant and the patient. An identity of the patient, including preferences and/or medical records, is maintained throughout interactions so that each aspect of this integrated system has access to the same information. The conversation user interface allows the patient to interact with the virtual assistant using natural language commands to receive information and complete a task related to his or her healthcare.

Abstract: The present invention allows for the capture and sentiment analysis of text the customer inputs into a chat, but never actually sends to the customer service representative (ghost text). The system captures this ghost text with a ghost capture system (GCS) software module. The GCS module analyzes the ghost text to generate metadata. The ghost text and metadata are used by a sentiment analysis engine to apply appropriate sentiment to the ghost text. The sentiment and ghost text are routed to a customer service representative (CSR). This provides the customer service agent with additional detail and information about a customer's emotions during a text chat conversation, allowing the CSR to determine a court of interaction not only based on the customer's response, but also based on the ghost text and the sentiment from the ghost text.

Abstract: A method of video operations includes generating derivative byproducts related to encoded video captured of a scene, initializing a first operation based on the encoded video, and initializing a second operation different from the first operation based on the derivative byproducts.

Abstract: Methods of intelligent routing of work assignment includes indexing plurality of pending tasks and indexing a plurality of available employees. A first employee is retrieved from an index of available employees. A next available task assignable to the first employee is determined. A work item for the next available task is assigned to the first employee from the available employee list. The assigned work item is removed from pending task list. The first employee is removed from the available employee list. The next employee is retrieved from the index of available employees.

Abstract: The system and method of the present application captures video of a scene in accordance with a plurality of capture characteristics, generates a capture profile for the video, and creates an index of the captured profile to enable a more rapid search of the captured video.

Abstract: The present invention allows a CEC system to automatedly, and without human intervention, identify interactions that are likely in need of supervisor intervention. The system reviews all incoming and outgoing interactions for analysis by a metadata analytics service (MAS) software module. The MAS analyzes the interactions to generate interaction metadata, which is used by an interaction analysis engine (IAE) to score the quality of the interaction. If the quality of the interaction is not sufficient, the system marks the interaction as being a problem interaction and notifies a supervisor of the interaction. This ensures the intelligent and dynamic determination of interactions that require additional assistance and assures notification to a supervisor.

Abstract: The present invention is a system and method for projective channel hopping within a customer engagement center (CEC) system. The CEC system receives a customer through a system entry point and receives, from the customer, a communication in a current customer service representative (CSR) channel in the CEC system. The CEC system assesses its ability to connect the customer with a CSR on the current CSR channel using a smart routing engine (SRE), which also assesses its current ability to connect the customer with a CSR on other equivalent CSR channels. Using the SRE, the CEC system compares its ability to connect the customer with a CSR on current and equivalent CSR channels to determine if the customer should remain on their current CSR channel or transfer to a new one. In the latter case, the CEC system offers the customer a chance to change channels or remain on their current channel.

Abstract: Virtual assistants intelligently emulate a representative of a service provider by providing variable responses to user queries received via the virtual assistants. These variable responses may take the context of a user's query into account both when identifying an intent of a user's query and when identifying an appropriate response to the user's query.

Abstract: Experiential parsing (EP) is a technique for natural language parsing that falls into the category of dependency parsing. EP supports applications that derive meaning from chat language. An experiential language model parses chat data, and uses documented experiences with language without using automatic natural language processing (NLP) methods. A descriptive grammar is built at word level rather than a prescriptive grammar at phrase level. The experiential model is designed to understand that word “A” associates with word “B” by function “C”. The experiential model understands the relationship between words, independent of whether or not the overall phrase structure is grammatical. A high accuracy of producing the syntactic roles (such as main verb, direct object, etc.) is attained even when confronted with a variety of agrammatical inputs.

Abstract: The present invention is a system and method of continuous sentiment tracking and the determination of optimized agent actions through the training of sentiment models and applying the sentiment models to new incoming interactions. The system receives conversations comprising incoming interactions and agent actions and determines customer sentiment on a micro-interaction level for each incoming interaction. Based on interaction types, the system correlates the determined sentiment with the agent action received prior to the sentiment determination to create and train sentiment models. Sentiment models include agent action recommendations for a desired sentiment outcome. Once trained, the sentiment models can be applied to new incoming interactions to provide CSRs with actions that will yield a desired sentiment outcome.