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: According to a first aspect, it is presented a method for dynamically selecting a learning model for a sensor device. The learning model is configured for determining output data based on sensor. The method comprises the steps of: detecting a need for a new learning model for the sensor device based on performance of a currently loaded learning model in the sensor device; determining at least one feature candidate based on sensor data from the at least one sensor, wherein each one of the at least one feature candidate is associated with a different source of sensor data; selecting a new learning model, from a set of candidate learning models, based on the at least one feature candidate and input features of each one of the candidate learning models; and triggering the new learning model to be loaded on the sensor device, replacing the currently loaded learning model.

Abstract: A hearing aid comprises an input unit providing an electric input signal representing sound, a wake word detector configured identifying a particular wake word based on said electric input signal, and providing a wake word control signal indicative of whether, or with what probability, the wake word is detected, or an own voice detector estimating whether, or with what probability, the electric input signal originates from the voice of the user and providing an own voice control signal indicative thereof, transceiver circuitry establishing a communication link to another hearing aid allowing the transmission and/or reception of the electric input signal to/from the other hearing aid, and a pre-processor controlling the transceiver circuitry in dependence of the wake word control signal or the own voice control signal. A binaural hearing aid system and a method of operating a hearing aid are further disclosed.

Abstract: Electronic communication methods and systems for rating agents and allowing customers for select agents are provided. Exemplary systems include a communication server for connecting a user to a communication with a contact center, a presence system to determine status of one or more agents, a wait-time determination engine to determine a wait time for one or more agents present for the communication, an agent scoring system for determining a score for one or more agents present for the communication, and a routing engine to connect a selected agent to the communication.

Abstract: A display device includes: a display panel; a first sound generator disposed on one surface of the display panel, where the first sound generator vibrates the display panel to output a first sound; and a first vibration damping member disposed between the display panel and the first sound generator, where the first vibration damping member reduces a vibration displacement of the display panel.

Abstract: Implementations are directed to using an assistant to initiate automated telephone calls with entities. Some implementations identify an item of interest, identify a group of entities associated with the item, and initiate the calls with the entities. During a given call with a given entity, the assistant can request a status update regarding the item, and determine a temporal delay before initiating another call with the given entity to request a further status update regarding the item based on information received responsive to the request. Other implementations receive a request to perform an action on behalf of a user, identify a group of entities that can perform the action, and initiate a given call with a given entity. During the given call, the assistant can initiate an additional call with an additional entity, and generate notification(s), for the user, based on result(s) of the given call and/or the additional call.

Abstract: A call management system of a call center retrieves from a customer database enterprise customer data associated with an identified customer in a customer call, which may include customer event data, attributions data, and activity event data. The customer database tracks prospects, leads, new business, and purchasers of an enterprise. The system retrieves customer demographic data associated with the identified customer. A predictive model is selected from a plurality of predictive models based on retrieved enterprise customer data. The selected predictive model, including a logistic regression model, and tree-based model, determines a value prediction signal for the identified customer, then classifies the identified customer into a first value group or a second value group. The system routes a customer call classified in the first value group to a first call queue assignment, and routes a customer call classified in the second value group to a second call queue assignment.

Abstract: A hearing device includes: a multi-chip assembly including a plurality of integrated circuit chips, the plurality of integrated circuit chips including one or a combination of a wireless communication chip, a power management chip, and a signal processing chip; wherein the multi-chip assembly comprises: a first layer having a surface, a spacer layer being configured to accommodate one or more of the plurality of integrated circuit chips as one or more embedded chips, and a ground layer below the first layer and the spacer layer, and a first shielding layer between the spacer layer and the first layer.

Abstract: Aspects of the subject disclosure may include, for example, a method of receiving, by a processing system including a processor, a call for a subscriber; determining, by the processing system, that the call is from an interactive voice response (IVR) system; determining whether the IVR system is providing a query that requires a response; and responsive to a first determination that the IVR system requires the response, providing the response. Other embodiments are disclosed.

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: The present disclosure relates to an RF antenna adapted to receive and/or transmit electromagnetic RF signals within a first frequency range enclosing a first frequency of resonance of the RF antenna, the RF antenna comprising: an electrically conductive antenna element having a feed for electrically connecting to an RF transmitter and/or an RF receiver; an electronic component adapted to receive and/or provide one or more electric signals from/to an electronic circuit within a second frequency range not overlapping the first frequency range; and one or more electric leads electrically connected to lead the one or more electric signals between the electronic component and the electronic circuit, each of the one or more electric leads being electrically connected to the electronic circuit through a respective inductor adapted to reflect and/or attenuate signals within the first frequency range and pass signals within the second frequency range.

Abstract: The technologies described herein are generally directed to modeling radio wave propagation in a fifth generation (5G) network or other next generation networks. For example, a method described herein can include, facilitating, by a first device, receiving a first communication directed to a second device from a third device associated with a first telephone number. The method can further include determining, by the first device, that the first communication comprises a reference to a second telephone number different from the first telephone number, resulting in a number discrepancy. Further, based on the number discrepancy and an analysis of the first communication, the method can further include preventing, by the first device, communication of the first communication to the third device.

Abstract: A system and method for domain adaptation involves a first domain and a second domain. A machine learning system is trained with first sensor data and first label data of the first domain. Second sensor data of a second domain is obtained. Second label data is generated via the machine learning system based on the second sensor data. Inter-domain sensor data is generated by interpolating the first sensor data of the first domain with respect to the second sensor data of the second domain. Inter-domain label data is generated by interpolating first label data of the first domain with respect to second label data of the second domain. The machine learning system is operable to generate inter-domain output data in response to the inter-domain sensor data. Inter-domain loss data is generated based on the inter-domain output data with respect to the inter-domain label data. Parameters of the machine learning system are updated upon optimizing final loss data that includes at least the inter-domain loss data.

Abstract: A method for estimating a global uncertainty of output data of a computer implemented main neural network. The method includes determining a first measure quantifying to which extent the current input data of the main neural network is following the same distribution as the data, which was used for training the main neural network; generating a second measure quantifying the main neural network's certainty in its own prediction based on the input data; ascertaining a third measure, based on an estimation of class-discriminative features in the input data and a comparison of these features with a class activation probability distribution, especially wherein the class activation probability distribution was created based on estimated class-discriminative features during the training of the main neural network; and determining the global uncertainty based on at least two measures of the first, second and third measure.

Abstract: Aspects of the disclosure relate to using machine learning for optimized call routing. A computing platform may receive requests to establish a voice call session. Based on corresponding phone numbers, the computing platform may identify demographic information for corresponding clients. Using a machine learning model and based on the demographic information and representative performance data, the computing platform may score potential client-representative combinations to indicate likelihoods of a successful outcome resulting from establishing a voice call session between the respective client and representative. Scoring the potential client-representative combinations may be based on fall off rates, indicating changes in representative effectiveness as hold time increases. The computing platform may adjust the scores based on a historical frequency of interaction between each representative and clients corresponding to the identified demographic information.

Abstract: The technology disclosed herein enables communications among users having communication session requests waiting in a queue. In a particular embodiment, a method includes determining that a first communication session request from a first endpoint is in a queue for establishing a communication session with a receiving endpoint to which the queue is regulating access. While the first communication session request is in the queue, the method includes connecting the first endpoint to a communication channel between the first endpoint and a second endpoint having a second communication session request in the queue. Also, while the first communication session request is in the queue, the method includes exchanging user communications between the first endpoint and the second endpoint over the communication channel.

Abstract: A method and system for providing a data consolidation for improved customer communication and agent performance evaluation in a multi-channel contact center are provided. The method includes receiving interaction data of an agent with customers across different communication channels within the contact center, consolidating the interaction data received across the different communication channels, aggregating the consolidated data to generate a set of metrics indicative of agent performance, inputting the set of metrics into an agent performance measurement framework, and determining a performance score for the agent based on an output of the agent performance measurement framework.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing a telephone call screener are disclosed. In one aspect, a method includes the actions of receiving a telephone call. The actions further include determining characteristics of the telephone call. The actions further include, based on the characteristics of the telephone call, determining a level of screening to apply to the telephone call. The actions further include determining screening data based on screening the telephone call according to the level of screening. The actions further include providing, for output, the screening data.

Abstract: A call management system of a call center identifies an inbound caller based upon computer analysis of customer identifiers, which may include at least two of customer name, street address, and zip code. Approximate string matching analysis matches n-grams generated from strings within customer identifiers, with n-grams generated from customer identification fields while searching one or more databases. Approximate string matching can incorporate a closeness metric based on Jaccard distance, and a Gaussian mixture model of best matches. In one embodiment, a polymr search engine analyzes customer identifiers of inbound callers to retrieve customer data, such as customer demographic data, matched to the customer identifiers. In another embodiment, the polymr search engine analyzes customer identifiers of inbound callers to identify repeat callers and retrieve previously collected customer data.

Abstract: A computer-implemented method is presented for selecting a preferred live agent from a plurality of live agents. The method includes constructing, via the processor, a human expertise matrix pertaining to each of the plurality of live agents by determining an average net promoter score (NPS) for each of the plurality of live agents for each category of a plurality of categories, and in response to a voice call by a user, determining, via the processor, a predicted human expertise on average by collectively assessing the human expertise matrix, a predicted NPS derived from a first deep neural network, and a predicted category derived from a second deep neural network. The method further includes, based on the predicted human expertise on average determined, triggering communication via the live agent communication network between the user and the preferred live agent to initiate a conversation between the user and the preferred live agent.