Abstract: A computer retrieves a dialog information records of the active call of the first operator. The computer extracts features from the dialog information records. The computer determines a feature vector from the extracted features and determines a transfer probability value based on the feature vector and previous call transfers to the second operator.

Abstract: Method starts with processing, by a processor, audio signal to generate audio caller utterance. Processor generates an agent action ranking score associated with the audio caller utterance and determines whether the agent action ranking score is below a minimum threshold. In response to determining that the agent action ranking score is below the minimum threshold, processor generates a transcribed caller utterance using a speech-to-text processor and generates an identified task based on the transcribed caller utterance. Using the transcribed caller utterance and a task-specific agent coaching neural network associated with the identified task, processor generates an ideal response. Processor generates a feedback result and causes the feedback result to be displayed on a display device of the agent client device. Other embodiments are disclosed herein.

Abstract: A method can be used for the generation of personalized Profile Package data in integrate circuit cards. A table includes data records corresponding to subscriptions to be generated. Each record includes personalization fields to store different types of personalization values. For a given subscription, a file for the Profile Package is in an ASCII format and includes fields to be personalized corresponding to one or more of the fields to store different types of personalization values. The file for the Profile Package in the ASCII format is converted into a hexadecimal code. An offset table is calculated for the given subscription indicating for each field to be personalized a corresponding offset in the hexadecimal profile. The personalization values from the personalization fields are substituted in the corresponding personalization fields to be personalized.

Abstract: An audio signal processing device comprises: a receiver for receiving an input audio signal; a processor for generating loudness metadata corresponding to the input audio signal; and an outputter for transmitting the loudness metadata generated by the processor. The processor is configured to acquire loudness information analyzed from input content, acquires loudness information about the input audio signal by measuring the loudness of the input audio signal, generates the loudness metadata by converting the loudness information, and transmits, through the outputter, the generated loudness metadata to an output device for outputting the input audio signal.

Abstract: An intelligent interface responds to text messages, which in a particular embodiment are addressed to a landline phone number. An IP network interface receives requests including a source phone number, message content and the destination phone number. The intelligent interface includes access to a serialized intent file created by a vectorizer. An intent classifier determines one intent from the serialized intent file based on the received message content. A response is generated according to the one intent. A reply generator generates a reply including the source phone number as a destination, the landline phone number as a source and the response.

Abstract: A method for providing coachable events for agents within a call center is provided. Behavior score waveforms for interactions and behaviors can be determined. Events can be identified in the behavior score waveforms within identified durations, and a relevancy of one or more events to one or more behaviors can be determined.

Abstract: A method of voice call diversion includes detecting an incoming voice call communication from a calling device, identifying an alternate communication option, providing the alternate communication option to the calling device, detecting a selection of the alternate communication option from the calling device, and diverting the incoming voice call communication so as to utilize the selected alternate communication option.

Abstract: Quality assurance systems are adapted to facilitate quality assurance of agents working in contact centers. According to at least one example, a quality assurance system may detect a script path employed by an agent through a pitch for at least one call, where the script path is represented by a sequence of agent keypresses associated with respective prerecorded audio scripts, navigations, and dispositions for the pitch. A determination may be made whether the detected script path employed by the agent through the pitch for the at least one call deviates from one or more standard profiles. At least one of the agent who conducted the at least one call or the at least one call may be flagged for further review when it is determined that the at least one call deviates from the one or more standard profiles. Other aspects, embodiments, and features are also included.

Abstract: Embodiments automatically establish a communication link with a conference platform using data received from a user device of a user. A conferencing device may interact with a user device to initiate a data transmission from the user device. An application on the user device may scan the contents of the user device for information associated one or more conference calls scheduled for a current time period. Upon identifying a matching conference call, the user device may transmit data associated with the conference call to the conferencing device. The application on the user device or the conferencing device may extract the call-in details (e.g. telephone number, conference code, conference PIN, URL or some other link to the conference) from the information associated with the conference call. The conferencing device may automatically initiate a call (e.g. establish the communication link) with the conference platform using the call-in details.

Abstract: A contact center system for performing call progress analysis including tone and speech classification according to an embodiment includes at least one processor and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the contact center system to determine a cumulative average of an entropy of an audio signal received by the contact center system, determine a cumulative average power spectral amplitude and a cumulative average spectral entropy of the audio signal, calculate a difference measure of the audio signal as a difference between the cumulative average of the entropy and the cumulative average spectral entropy, distinguish tones from speech of the audio signal based on the difference measure, and process one or more tones of the audio signal in response to identification of the one or more tones in the audio signal.

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: Work support system and method with screen sharing and development system for multi-platform application disclosed. The work support system with screen sharing includes a customer terminal in which a service application is installed and executed, an employee terminal configured of sharing and displaying a designated area of an execution screen of the service application, and a work support server configured of communicating with the customer terminal and the employee terminal, and supporting a customer work by setting a screen of the customer terminal to be shared in the employee terminal under a specified condition.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining a transfer option for transferring a call. One of the methods includes: dynamically capturing, by the at least one processor, during a call between a first individual and a second individual, one or more keywords from a verbal conversation between the first individual and the second individual during the call; automatically determining, by the at least one processor, a transfer option for transferring the call based on the captured one or more keywords; and transferring, by the at least one processor, the call to a transfer unit specified by the determined transfer option.

Abstract: A method for providing anonymized contact information to a workforce management system includes receiving contact information from a plurality of customer business units; assigning each of the plurality of customer business units one or more industry classification codes or product classification codes; anonymizing, by a processor, the contact information to the one or more industry classification codes or product classification codes; receiving, by a processor, a query from a workforce management system for anonymized contact information in one or more industry classification codes or product classification codes; and providing the anonymized contact information to the workforce management system for use in a workforce management predictive model.

Abstract: Techniques are described for generating metrics about an individual's experience. One of the method describes providing, by at least one processor, the session record as input to at least one computer-processable model that determines, based on the session record, at least one metric for the service session, the at least one model having been trained, using machine learning and based at least partly on survey data for previous service sessions, to provide the at least one metric associated with the individual's experience. The method includes associating, by at least one processor, the metric of the individual's experience with the individual. The method also includes communicating, by at least one processor, the at least one metric for presentation through a user interface of a computing device.

Abstract: Techniques for estimating expected performance of a task assignment strategy in a task assignment system are disclosed. In one particular embodiment, the techniques may be realized as a method comprising receiving, by at least one computer processor communicatively coupled to a task assignment system, a plurality of historical agent task assignments; determining, by the at least one computer processor, a sample of the plurality based on a strategy for pairing agents with tasks; determining, by the at least one computer processor, an expected performance of the strategy based on the sample; outputting, by the at least one computer processor, the expected performance; and optimizing, by the at least one computer processor, the performance of the task assignment system based on the expected performance.

Abstract: A method, system and program product, the method comprising: obtaining for each call in one set of calls a respective pattern representing multiple different respective data fields; obtaining performance data for the respective patterns of the calls; obtaining performance data for the respective agents; determining agent performance sensitivity to call pattern performance for agents in a set of agents comprising the agent performance data correlated to call performance data for the calls the agent handles; and matching a respective one of the agents from the set of agents to one of the calls based at least in part on the performance data for the respective pattern of the one call and on the agent sensitivity to call performance for the respective one agent of the set of agents.

Abstract: Disclosed herein is a method for automated agent behavior recommendations for call quality improvement. The method performed at a server includes receiving a first data record and a second data record of a plurality of data records, each comprising communication between a first party and a second party and determining a first communication originated from the first party. The method includes determining a category for each section of the plurality of sections of the first communication, and a plurality of behavior distances between different categories associated with the plurality of sections. The method includes augmenting first metadata of the first data record and second metadata of the second data record to include associated behavior distances and determining an average performance ranking of the first party to generate a recommendation to increase the average performance ranking of the first party above a preconfigured threshold.

Abstract: A voice call conversion system includes an interactive voice response app offering the voice caller an option to engage in a texting session with an intelligent interface on an application server. A telephony server connected to the telephone network receives voice calls and communicates with the application server to initiate an interactive voice response session. The texting session can take place even if the call was placed to a landline phone number. A gateway converts text messages on a cellular network to requests on an IP network and in the opposite direction converts IP network communications to text messages on the cellular network.

Abstract: A system for quickly deploying QM systems in contact centers is provided. A user or administrator can quickly install a QM application on a deployment server. The administrator can provide the QM application access to the contact center data where the QM application can import data from the contact center routing system about one or more customers, agents, queues, teams, and any other information or items typically associated with contact center routing systems. The imported data may also include presence data about the agents, teams, and customers. Based on the imported data, the QM application may execute one or more workflows to automatically determine information such as evaluation frequency and coaching frequency about the agents and teams, or to create or select quality forms to use for the evaluation one or more agents, teams, or contacts.