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; calculating, by the data calculation engine, a priority of the call interaction from the text and organization, location, and time information in the text by determining an important of words in the text and correlating the words to a priority class using a pre-trained algorithm that is trained on emergency-type and emergency services-type language; determining that the call interaction should be transmitted to 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: A covert sports communication system has a transmitter configured to wirelessly transmit coded audio track selection signals. The system includes a receiver that may be worn within headgear. The receiver includes stored audio tracks and is configured to receive coded audio track selection signals from the transmitter, decode the audio track selection signals, and play at least one stored audio track in accordance with the decoded audio track selection signals. The audio tracks may include audio instructions to a participant of a sporting event.

Abstract: A telephone subnet crawler is used to access automated telephone response systems and index the information, contents and structure contained therein. A database of the information, contents and structure of a plurality of automated telephone response systems is created by the telephone subnet crawler. A user interface provides a waiting party with direct access to the information, contents and structure of the automated telephone response systems contained in the database. Where an automated telephone response system requires user input, the user interface calls the automated telephone response system and navigates to the node requiring user input, provides the user input and displays the results to the user. Where an automated telephone response system connects to an operator, the user interface calls the automated telephone response system, navigates to the node for an operator, and when an operator is detected, calls the user at a user provided callback number.

Abstract: A contact center system uses user profiles and agent profiles to determine a routing for a contact center engagement request from a user device to an agent device. Responsive to the contact center engagement request, a user profile associated with the user device is accessed to determine a prioritization score. The prioritization score can be determined in some cases using both information associated with the user profile and input obtained from the user device. Agent profiles are accessed to determine an agent to support the contact center engagement request based on the prioritization score. Each of the agent profiles corresponds to a different contact center agent or agent group. The determined agent may be selected from amongst a plurality of candidates identified based on the profile evaluation. A private session is then established between the user device and a device of the agent.

Abstract: In an example embodiment, a solution is provided that introduces a second level IVR component controlled by a call control service that also controls a first IVR component. Controlling the IVR components using this call control service (which also interfaces with client software operated by a human agent) allows for data collected during the IVR sessions or during a live session with the human agent to be shared among the components. This also acts to eliminate the need for a traditional “transfer” of a call from a human agent to an IVR or vice versa, which would often be accompanied by audible clicks or beeps discernable to the caller.

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: Systems and methods forecast inbound telecommunications, and more particularly, analyze real-time and historical call center data, and apply a forecasting model to the data in order to predict inbound call volume. These systems and methods employ tools that manipulate call center data and generate visual representations of metrics pertaining to forecasting call center data via a dashboard.

Abstract: Systems and methods include generating an urgency score associated with data associated with a communication session based on processing the data and using the urgency score to modify a behavior of a bot or a call center agent and optimize a contact center. Systems and methods include modifying behavior of a bot or an agent during the communication session in response to the data. Systems and methods include modifying dialog of a bot, or a script of an agent, and modifying a control flow for the communication session. Optimizing a contact center includes adjusting a workload of an agent associated with the communication session.

Abstract: An adaptive cloud conversation ecosystem that expands on the capabilities of an adaptive cloud conversation platform by allowing for integration of conversations across brands with a single consumer account and incorporation of edge computing data from multiple consumer devices into brand and consumer decision-making. The core of the ecosystem is an adaptive cloud conversation platform capable of making automated decisions regarding when and how to establish on-going communications with consumers so as to maximize the relationship between the consumer and a given brand. Adaptive ecosystem applications expand on the capabilities of platform by providing context-specific utilities that are compatible with platform and therefore capable of applying the adaptive conversation platform's capabilities to a variety of subject matters.

Abstract: In the field of government engagement management, an agent guide or script-flow in an employee desktop web client is implemented. In such a system and method, when agents create interactions with clients they can follow a script-flow which will guide the agent through the interaction through a series of menu selections and automated sets of instructions. This feature of the government engagement management system allows existing customer investment from the rich desktop client or non-web client in developing specific scripts, that can also now function in the web client atmosphere. This system and method also enables an agent to handle calls with the web client more efficiently, and allows agents on the web client to automatically classify.

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: A computer-implemented method for providing an objective evaluation to a customer service representative regarding his performance during an interaction with a customer may include receiving a digitized data stream corresponding to a spoken conversation between a customer and a representative; converting the data stream to a text stream; generating a representative transcript that includes the words from the text stream that are spoken by the representative; comparing the representative transcript with a plurality of positive words and a plurality of negative words; and generating a score that varies according to the occurrence of each word spoken by the representative that matches one of the positive words, and/or the occurrence of each word spoken by the representative that matches one of the negative words. Tone of voice, as well as response time, during the interaction may also be monitored and analyzed to adjust the score, or generate a separate score.

Abstract: A system for selecting communication routes based on multiple criteria may allow users to configure call routing systems to dynamically route calls by performing one or more of: ranking call destinations (e.g., vendors or trunk locations), adjusting or replacing route groups, queuing calls, activating interactive voice responses (IVRs), and re-purposing ports and trunks.

Abstract: An adaptive cloud conversation platform capable of making automated decisions regarding when and how to establish ongoing communications with consumers so as to maximize the relationship between the consumer and a given brand. The system has a connection management services layer which determines what communications should be established and how they should be established, an initiation management services layer which determines when communications should be established, and a user management services layer which stores information about consumers and brands for determination of when and how communications should be established. Certain of these services have machine learning algorithms incorporated into them trained to perform analyses of the particular type of operation handled by that service. The outputs of each service can be used as inputs to other services, such that a network of machine learnings algorithms is created which determines when and how to establish ongoing communications with consumers.

Abstract: Various example implementations are directed to methods and apparatuses for facilitating conferenced communications. In one of various examples involving audio signals received from a plurality of participants of a digital audio conference, a logic circuit is to process the audio signals via respective audio input circuits respectively associated with each of the endpoint devices, and, in response to a subset of the different audio signals deemed or qualified as having a loudest audio input, encodes audio from only the subset for broadcasting to participants of the digital audio conference.

Abstract: A system and method for managing virtual queues. A cloud-based queue service manages a plurality of queues hosted by one or more entities. The queue service is in constant communication with the entities providing queue management, queue analysis, and queue recommendations. The queue service is likewise in direct communication with queued persons. Sending periodic updates while also motivating and incentivizing punctuality and minimizing wait times based on predictive analysis. The predictive analysis uses “Big Data” and other available data resources, for which the predictions assist in the balancing of persons across multiple queues for the same event or multiple persons across a sequence of queues for sequential events.

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: Machine learning technology can analyze in real-time the data from a call between a person and a customer service representative. Based on this analysis, a server can determine a sentiment score that describes a sentiment expressed by the person or the customer service representative. If the server determines that the sentiment score is less than or equal to a pre-determined value, the server can inform the customer service representative's manager so that the manager can take further action to help the person and/or the customer service representative.

Abstract: A conference device and a computer-implemented method for training a neural network are disclosed, the conference device comprising a conference controller; a microphone array comprising a plurality of microphones for provision of audio signals representing audio from one or more sound sources; a direction estimator connected to the conference controller and the microphone array, the direction estimator configured to obtain, from the microphone array, a plurality of audio signals including a first audio signal and a second audio signal; determine direction data based on the plurality of audio signals, the direction data comprising an indication of an estimated probability of voice activity for one or more directions, wherein to determine direction data comprises to apply an offline-trained neural network; and output audio data based on the direction data to the conference controller.

Abstract: A system and method for managing virtual queues. A cloud-based queue service manages a plurality of queues hosted by one or more entities. The queue service is in constant communication with the entities providing queue management, queue analysis, and queue recommendations. The queue service is likewise in direct communication with queued persons. Sending periodic updates while also motivating and incentivizing punctuality and minimizing wait times based on predictive analysis. The predictive analysis uses “Big Data” and other available data resources such as schedule data and historical throughput data for various resources associated with an entity, for which the predictions assist in the balancing of persons across multiple queues for the same event or multiple persons across a sequence of queues for sequential events.