Abstract: An image processing system includes a server, an image processing device, a mobile terminal, and a call center terminal. When switching from a response by a chatbot to a response by an operator is executed, the server transmits a response history of the chatbot to the call center terminal so that the call center terminal may check the response history of the chatbot. The entire response history of the chatbot is presented to the operator when the amount of information on the response history of the chatbot is equal to or less than a predetermined threshold, and a summary of the response history based on the response history of the chatbot is presented to the operator when the amount of information on the response history of the chatbot is more than the threshold.

Abstract: A system for dynamically routing customer calls. For example, the system may receive user interaction data associated with a first user using a first user device. The system may also receive a phone call from a user using a first phone number. The system may also identify the user via the first phone number. The system may determine, using a first machine learning model, whether the first user has a first emotion type based on the user interaction data. When the first user does not have the first emotion type, the system may route the first user to any call center representative. When the first user has the first emotion type, the system may route the first user to a first call center representative among one or more first call center representatives.

Abstract: A method operates a hearing system which has a hearing instrument worn in an ear. The method includes capturing a sound signal from an environment, processing the captured sound signal in dependence of a set of signal processing parameters, and outputting a processed sound signal to the user. The method further includes analyzing the captured sound signal to recognize own-voice intervals, in which the user speaks, analyzing the captured sound signal for an acoustic feature of the own voice of the user and/or analyzing a signal of a bio sensor. The bio sensor measures at least one non-acoustic vital function of the user and determines, from the acoustic feature and/or the non-acoustic vital function of the user, a measure of an emotional state of the user. A value of a signal processing parameter is adapted, within the own-voice intervals, to change the emotional state if a criterion is fulfilled.

Abstract: A contact center, communication system, and method of operating a contact center are provided. In one example, the contact center includes a plurality of chatbots stored in memory and a chatbot selector that determines a customer interaction in the contact center will have a chatbot assigned thereto, selects a chatbot from the plurality of chatbots for assigning to the customer interaction based on a match between a capability of the chatbot and a service requirement associated with the customer interaction, and assigns the selected chatbot to the customer interaction thereby enabling the selected chatbot to process inputs received during the customer interaction and provide responses to the inputs.

Abstract: Systems for and methods of determining the priority of a call interaction include receiving a call interaction from a call center; validating, by a validation and transcription engine, that the call interaction is authentic; converting, by the validation and transcription engine, the call interaction into text; extracting, by a data calculation engine, organization, location, and time information from the text; calculating, by the data calculation engine, a priority of the call interaction from the extracted information and the text; determining that the call interaction should be transmitted to a queue of the call center for initial handling by a call center agent; and transmitting the call interaction, the calculated priority, and the extracted information to the call center.

Abstract: Systems, methods, and computer program products include smart capacity workload routing with workload modeling. One example involves storing a workload model in memory regarding a set of different factors associated with user communications, with each factor is associated with a measurement of workload. A received request including information regarding one or more of the factors is processed and used in identifying a workload measurement for the requested user communication based on comparing the received request information to the stored workload model. An agent with capacity that is available to handle the requested user communication is identified. A communication slot for the identified agent is activated and defined by the identified workload measurement, and the request is routed to the identified agent and updating available workload capacity in the system.

Abstract: A method for resolving customer requests that includes: providing a personal bot assistant and an asynchronous resolution facilitator; receiving a customer request from a first customer and producing a transcript thereof; determining an intent based on the transcript and customer information relating to the determined intent; transmitting an initial set of data to the asynchronous resolution facilitator and assembling therefrom a resolution package that includes an agent interface showing information required to expeditiously resolve the customer request including one or more recommended business processes; displaying the agent interface on a screen of the agent device; receiving input from the agent device that indicates the agent has completed preparing a resolution for the customer request; and providing notification to the first customer of the achieved resolution via the personal device of the first customer.

Abstract: Systems and methods for using machine-learning techniques for labeling incoming calls with categories relating to a risk level. A model is generated using call log data. The call log data is augmented using information from additional data sources to generate features for the model. The model may then be used to categorize additional incoming calls. The model may be used in real-time to categorize incoming calls, or categorization results may be stored for a plurality of calling numbers. Various embodiments provide various technical advantages by virtue of how the components of the system are deployed between an endpoint communication device, a telephony provider system, and possibly other systems.

Abstract: Automated monitoring of a voice communication session, when the session is in an on hold status, to determine when the session is no longer in the on hold status. When it is determined that the session is no longer in the on hold status, user interface output is rendered that is perceptible to a calling user that initiated the session, and that indicates that the on hold status of the session has ceased. In some implementations, an audio stream of the session can be monitored to determine, based on processing of the audio stream, a candidate end of the on hold status. In response, a response solicitation signal is injected into an outgoing portion of the audio. The audio stream can be further monitored for a response (if any) to the response solicitation signal. The response (if any) can be processed to determine whether the end of the on hold status is an actual end of the on hold status.

Abstract: There is provided an information processing system including a storage section that holds a plurality of agent programs with different attributes, a communication section that provides an agent service by the agent programs to a client terminal of a user, and a control section that selects, from among the plurality of agent programs, one agent program suited to an emotion of a user who can use the agent service.

Abstract: Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, and/or computing entities for processing performance metric recommendations for an agent profile.

Abstract: A method comprises establishing a communication session between an agent and at least one of a caller and a called party. The method comprises establishing a communication session between an agent and at least one of a caller and a called party and monitoring the communication session for one or more audit triggers. The method comprises detecting the one or more audit triggers. The method comprises, in response to detecting the one or more audit triggers, sending a notification to a client, the notification identifying one or more communication session auditing procedures available for the communication session. The method comprises receiving, from the client in response to the notification, a request to audit the communication session using at least one of the available one or more communication session auditing procedures. The method comprises performing the requested at least one communication session auditing procedure.

Abstract: Systems and methods are used to generate contact type predictions that route user customer service requests within a support platform. The contact type predictions are generated using a hybrid model that includes a deep learning component and a business logic component. The deep learning component may generate a multi-channel output based on text features and context features. The multi-channel output is modified based on one or more business rules to generate the contact type predictions.

Abstract: In order to provide effective communications, the individuals engaged in the communication should have appropriately matched language proficiencies. By ensuring that a customer of a contact center is matched with an agent having, or presenting, content of a communication utilizing language proficiency appropriate for the customer, effective communications may be provided. Should an agent deviate and provide communication content having language proficiency that is misaligned with the customer, automatic corrective action may be taken to realign the language proficiency presented to the customer.

Abstract: A method and system are described that interact with a self-service system on behalf of a customer and without requiring a presence of the customer during the interactions. An illustrative method includes receiving one or more inputs from a customer, where the one or more inputs define a desired action to take on behalf of the customer with the self-service system in the absence of the customer's presence, obtaining contact information for the self-service system, using the contact information to automatically establish a communication session with the self-service system, receiving a prompt from the self-service system, and performing the desired action as a response to the prompt, where the desired action is performed during the communication session on behalf of the customer and in the absence of the customer's presence.

Abstract: Method, computer program product, and system for augmenting a voice call with a user interface to provide a user visual access to a guided solution. The user interface is generated based on information such as a spoken language string received from a user using a user device with a display. The user interface including user interface elements for the guided solution is provided to the user via the display of the user device such that the user proceeds through the guided solution using the user interface during the voice call.

Abstract: A method and apparatus for predicting customer behavior is disclosed. The method comprises organizing a transcribed, diarized text of a conversation in a call, into a predefined number of sets, determining features corresponding to a sentiment score, a percentage and/or count of positive words, and a percentage and/or count of negative words for each of the a predefined number of sets, determining word count features corresponding to the word count for each of the a predefined number of sets, determining features corresponding to a call talk time, a call hold time and a call hold percentage based on the transcribed text. Based on all the determined features, the method determines whether the customer is satisfied or not, the customer activity based on an activity profile of the customer, and whether the customer used escalation terms based on the transcribed text.

Abstract: Method, apparatus, and program code embodied in computer-readable media, for providing enhanced echo suppression in a conferencing system having at least one microphone and at least one speaker. At least one microphone input signal is received, and at least one speaker input signal is provided. At least one processor has at least one primary echo-suppressor and at least one secondary echo-suppressor. The at least one primary echo-suppressor receives (i) the microphone input signal(s) and (ii) the speaker input signal(s). The at least one primary echo-suppressor provides at least one echo-suppressed microphone signal. The at least one secondary echo-suppressor receives the at least one echo-suppressed microphone signal and provides an output signal. The at least one processor provides the at least one echo-suppressed microphone signal to the at least one secondary echo-suppressor without providing the at least one speaker input signal directly to the at least one secondary echo-suppressor.

Abstract: An audio processor for providing loudspeaker signals on the basis of input signals, like channel signals and/or object signals, obtains an information about the position of a listener and an information about the position of a plurality of loudspeakers, or sound transducers. The audio processor selects one or more loudspeakers for a rendering of the objects and/or of the channel objects and/or of the adapted signals, derived from the input signals. The selection depends on the information about the position of the listener and about the positions of the loudspeakers and takes into consideration the information about one or more acoustic obstacles. The audio signal processor renders the objects/channel objects/adapted signals derived from the input signals, in dependence on the information about the position of the listener and about positions of the loudspeakers, in order to obtain the loudspeaker signals, such that a rendered sound follows a listener.

Abstract: A system and method of use to train customer service agents. The training system employs intelligent systems to facilitate or enable the training of customer service agents. The training system provides training to customer service agents and tracks the progress of the customer service trainees. In one aspect, the training system emulates a customer engaging with the customer service trainee, by emulating one or both of the persona of the customer and the scenario of the customer/trainee interaction.