Abstract: Methods and systems are provided for the AI-based computer-aided persuasion system (CAPS). The CAPS obtains inputs from both the target and the agent for an object, dynamically generates persuasion references based on analysis of the input. The CAPS obtains content output by analyzing the agent audio stream and the target audio stream using a recurrent network (RNN) model, obtains sentiment classifiers based on a convolutional neural network (CNN) model, updates a conversation matrix, and generates a persuasion reference based on the updated conversation matrix. The persuasion reference is based on an acceptance likelihood result generated from the conversation matrix using the RNN model. The CAPS further generates a target profile using CNN with input of target Big Data, wherein the target profile includes one or more objects, and wherein the agent is selected based on the generated profile and one or more selected objects.

Abstract: A method, a device, a system for analyzing comment data about a target are provided. The method includes acquiring the comment data about the target in accordance with a link to the target; and analyzing the comment data and determining a comment topic and a comment viewpoint about the target.

Abstract: Conversation support systems and methods are operable to assist a user to more fully participate in an ongoing conversation. An exemplary embodiment receives a conversation map comprising a serially arranged plurality of conversation segments of audio information each associated with one of a plurality of conversation participants, and that includes dialogue of the ongoing conversation being spoken by the associated conversation participant; determining subject matter of a current portion of the ongoing conversation based on the dialogue; selects conversation support information that pertains to the current conversation subject; and generating a conversation queue that includes information that corresponds to the selected conversation support information, wherein the conversation queue is communicated from the conversational support system to at least one conversation queue output device that presents the conversation support information to the user.

Abstract: A caption of a multimodal message (e.g., social media post) can be identified as a named entity using an entity recognition system. The entity recognition system can use a visual attention based mechanism to generate a visual context representation from an image and caption. The system can use the visual context representation to identify one or more terms of the caption as a named entity.

Abstract: Systems, methods, computer systems, and computer-readable code for implementing methods for client relation management in which fewer call-in numbers need to be maintained. A method for client relation management preserves a more-complete record of online and offline interactions of a customer with systems provided by a plurality of service providers. A session identifier (SID) is associated with a customer upon interaction of the customer with a website provided by a first service provider. Website interaction information is received from the first service provider and is associated with the SID. Information associated with an incoming call from the customer at a call-in number at a call center maintained by a second service provider is used to associate the incoming call with the SID, creating a record of an offline interaction between the customer and an agent of the call center. The record of the offline interaction is associated with the SID.

Abstract: Non-limiting examples of the present disclosure describe insight-based routing that is used to improve processing of a service request through a help desk service. A request for support (e.g. technical support) can be received through a modality of a help desk service. The request is evaluated, where an evaluation of the request comprises analyzing an issue associated with the request as well as user-specific signal data associated with a customer and generating insights. A support agent is matched to the customer based on an evaluation of the request. The support agent is selected from a pool of support agents based on application of a model that analyzes support agent data in correlation with the generated insights. An interaction between the matched support agent and the customer may be initiated through a modality of the help desk service.

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: Certain aspects of the disclosure are directed to apparatuses and methods involving a data-communication apparatus that includes a data-communications server and processing circuitry in communication therewith. The data-communication server interfaces with a plurality of remotely-situated client entities for providing data communication services. The processing circuitry accesses an archive of digital voice data indicative of transcribed audio conversations for at least one of the plurality of remotely-situated client entities, calendar information, and a client data-communications server for geographic information of the agents and system parameters. The processing circuitry analyzes the digital voice data associated with the agents, the calendar information, and the system parameters to predict a call answer rate for agents of a geographic region of the at least one remotely-situated client entity for a period of time and reroutes incoming calls based on the predicted call answer rate.

Abstract: A system herein provides automated call-back of customers who have terminated an inbound call by exercising a call-back option of an interactive voice response unit or by abandoning the inbound call, using predictive modeling of caller value to prioritize call-backs. The call management system monitors the inbound customer call and detects any termination of the customer call. A call-back module opens a call-back record for the terminated customer call and associates that call-back record with an identified customer. The call-back module retrieves customer demographic data and other data associated with the identified customer. A predictive module determines a value prediction signal for the identified customer by modeling purchase and lapse behaviors and classifies each identified customer for either priority call-back or subordinate call-back treatment.

Abstract: Methods, systems, and articles of manufacture for ranking individuals in a contact center system including ranking a first individual in a set of individuals based on relative amounts of data for the first individual and one or more other individuals in the set of individuals.

Abstract: A conversation may be monitored in real time using a trained machine learning model. This real-time monitoring may detect attributes of a conversation, such as a conversation type, a state of a conversation, as well as other attributes that help specify a context of a conversation. Contextually appropriate behavioral targets may be provided by machine learning model to an agent participating in a conversation. In some embodiments, these “behavioral targets” are identified by applying a set of rules to the contemporaneously identified conversation attributes. The behavioral targets may be defined in advance prior to the start of a conversation. In this way, the machine learning model may be trained to associate particular behavioral target(s) with one or more conversation attributes (or collections of attributes). This facilitates the real-time monitoring of a conversation and contemporaneous guidance of an agent with machine-identified behavioral targets.

Abstract: Embodiments include techniques to generate alerts based at least in part on predicted mood responses to received electronic communications that include receiving, using a processor system, a communication, and analyzing, using the processor system, contents of the communication. The techniques also include based at least in part on results of the analysis, predicting, using a machine learning system, a cognitive response of a recipient of the communication, and based at least in part on the predicted cognitive response, executing an alerting operation.

Abstract: The present invention relates to communications methods and apparatus for determining whether a received call originated from an artificial intelligence system and the call handling procedures to be used on the received call based on whether or not the call was determined to have been originated from an artificial intelligence system. An exemplary method embodiment includes the steps of: receiving a first call; determining whether said first call originated from an artificial intelligence system; and when said first call is determined to have originated from an artificial intelligence system performing one or more artificial intelligence call handling operations.

Abstract: Methods, systems, and computer program products controlling navigation of a visual aid during a presentation are provided. An example method includes monitoring, speech of an individual during the presentation. Evaluating one or more verbal and visual cues indicative of an end of a slide of a plurality of slides of the visual aid. Predicting a probability of changing the slide to a next slide of the plurality of slides in a predetermined amount of time, in which the probability is predicted based, at least in part, on the evaluated one or more verbal and visual cues. Displaying the next slide at the predetermined amount of time from the predicting.

Abstract: Provided is a speech recognition method for a recognition target language. According to an embodiment of the inventive concept, a speech recognition method for a recognition target language performed by a speech recognition apparatus includes obtaining an original learning data set for the recognition target language, constructing a target label by dividing the text information included in each piece of original learning data in letter units, and building an acoustic model based on a deep neural network by learning the learning speech data included in the each piece of original learning data and the target label corresponding to the learning speech data.

Abstract: An auditory prosthesis can be powered by an on-board battery that is placed into a receptacle in the auditory prosthesis. When longer battery life is desired, a recipient can selectively utilize a discrete power supply to power the auditory prosthesis. The discrete power supply provides power to the auditory prosthesis and, in certain embodiments, has a longer life than the on-board battery. The discrete power supply includes an adapter having a form factor that mates with the battery receptacle on the auditory prosthesis.

Abstract: A method for routing customer service requests to call centers includes collecting data associated with customer service experience between a customer and a call center regarding a completed customer call. The collected data is analyzed to determine a quality of customer service for one or more completed calls between the customer and the call center. A nature of an incoming customer call is determined. The incoming customer call is routed to a call center based upon making reference to the analyzed collected data such that the nature of the customer call matches with corresponding one or more favorable attributes of the call center.

Abstract: The present invention relates to methods and apparatus for dynamically detecting and/or mitigating threats in communications systems. Exemplary methods and apparatus of the present invention allow for a combination of automated and operator controlled responses to threats. While an operator is provided an opportunity to provide input on how to respond to a threat, after one or more threats of a given type are identified, the system will automatically take corrective action without waiting for operator input and/or in the absence of operator input following notification of a threat.

Abstract: A terminal includes a memory configured to store voice data and a processor configured to measure reliability of learnable data stored in the memory, to classify the learnable data into learning data or adaptive data according to the measured reliability, to generate a learning model by performing unsupervised learning with respect to the learning data, to generate an adaptive model using the adaptive data, and to evaluate recognition performance of each of the learning model and the adaptive model.

Abstract: The present disclosure provides, among other things, a method of managing a wrap-up time in a contact center, the method including: receiving, by an agent of the contact center, a communication having a variable associated with the communication; receiving an input from a source external to the contact center; determining that the variable is related to the input; based on the relation of the variable to the input, determining an updated wrap-up time; storing the updated wrap-up time and the input in a database including timing variables; enabling a machine learning process to analyze the database; providing the updated wrap-up time to the agent as an amount of time rendered on a display to the agent; and updating a data model used to automatically determine wrap-up times based on the analysis of the machine learning process.