Abstract: A computerized-method for calculating an agent skill-satisfaction-index and utilization thereof, is provided herein. The computerized-method includes operating an Agent-Skill-Satisfaction-Index (ASSI)-scoring module.

Abstract: A method of assisting an agent in real-time includes receiving a call interaction between a customer and an agent; identifying words spoken in the call interaction; providing the words to a behavioral models module; computing a score for a plurality of behavioral metrics; providing a phrase formed by the words to a knowledge article selection module; providing each score for the plurality of behavioral metrics to the knowledge article selection module; providing a plurality of knowledge selection rules to the knowledge article selection module; evaluating a combination of the phrase and the scores of the plurality of behavioral metrics against each of the plurality of knowledge selection rules; matching a knowledge selection rule to the combination; selecting a knowledge article associated with the matched knowledge selection rule; generating a visual representation of the selected knowledge article; and presenting in real-time the visual representation on a graphical user interface.

Abstract: A system and method may identify a fraud ring based on call or interaction data by analyzing by a computer processor interaction data including audio recordings to identify clusters of interactions which are suspected of involving fraud each cluster including the same speaker; analyzing by the computer processor the clusters, in combination with metadata associated with the interaction data, to identify fraud rings, each fraud ring describing a plurality of different speakers, each fraud ring defined by a set of speakers and a set of metadata corresponding to interactions including that speaker; and for each fraud ring, creating a relevance value defining the relative relevance of the fraud ring.

Abstract: A computer based system and method for identifying complaint interactions, including: detecting appearances of linguistic structures related to complaints in an interaction; calculating at least one sentiment metric of the interaction; and classifying the interaction as being or not being a complaint interaction based on the detected linguistic structures and the at least one sentiment metric, for example using a trained supervised learning model.

Abstract: Methods for voice authentication include receiving a plurality of mono telephonic interactions between customers and agents; creating a mapping of the plurality of mono telephonic interactions that illustrates which agent interacted with which customer in each of the interactions; determining how many agents each customer interacted with; identifying one or more customers an agent has interacted with that have the fewest interactions with other agents; and selecting a predetermined number of interactions of the agent with each of the identified customers. In some embodiments, the methods further include creating a voice print from first and second speaker components of each interaction; comparing the voice prints of a first selected interaction to the voice prints from a second selected interaction; calculating a similarity score between the voice prints; aggregating scores; and identifying the voice prints that are associated with the agent.

Abstract: Systems and methods are provided for solving workforce management scheduling optimization decomposing and iteratively. Execution of a master problem can occur to select a best schedule among generated schedules for each employee of a group of employees while enforcing one or more global constraints. The generated schedule can be determined by execution of one or more sub-problems, each of the one or more sub-problems can be enforced work rules for the respective employee through the use of reduced cost for the employee. A flexible objective function can be executed to account for workforce management schedule wide metrics, including fitness of schedule to demand, fairness among the group of employees, schedule preferences and others.

Abstract: A system and method for real-time fraud detection with a social engineering phoneme (SEP) watchlist of phoneme sequences may perform real-time fraud prevention operations including receiving incoming call interactions and grouping the call interactions into one or more clusters, each cluster associated with a speaker's voice based on voiceprints. For a pair of voiceprints in a cluster, a phoneme sequence is extracted for each voice print. From the extracted phoneme sequences, a similarity score is then calculated to determine if a match exists between the extracted phoneme sequences based on a threshold. If determined a match exists, the phoneme sequence may be added to a SEP watchlist.

Abstract: A system and method for classification of voice samples to genuine voice samples or spoofing voice samples may include: extracting a set of features from each of a plurality of voice samples, each voice sample labeled as genuine or spoof; training a neural network having a plurality of nodes organized into layers, with links between the nodes, wherein each link comprises a weight, with the sets of features, by adjusting at least one of the weights using a loss function that comprises a regulation factor, wherein the regulation factor is set to zero for voice samples labeled as genuine and is proportional to the prediction of the neural network for data samples labeled as spoofing.

Abstract: A computer based system and method for identifying complaint interactions, including: detecting appearances of linguistic structures related to complaints in an interaction; calculating at least one sentiment metric of the interaction; and classifying the interaction as being or not being a complaint interaction based on the detected linguistic structures and the at least one sentiment metric, for example using a trained supervised learning model.

Abstract: Systems and methods of managing customer journeys are implemented using one or more processors in a computing system. Each journey may comprise a succession of interactions at interaction points such as telephone conversations, responses to an interactive voice response “IVR” system and viewing a web page. Customer journey scores are determined for customers at one or more interaction points along the customer journey and the customer journey score is used to determine whether and when an intervention should take place. Models for determining customer journey scores may be created for a set of customers based on one or both of subjective and objective data relating to a subset of the set of customers that have made some or part of the journey, e.g. customers that have responded to polls. An intervention may take place during the journey or after completion of the journey.

Abstract: A computerize method for voice authentication of a customer in a self-service system is provided. A request for authentication of the customer is received and the customer is enrolled in the self-service system with a text-independent voice print. A passphrase from a plurality of passphrases to transmit to the customer is determined based on comparing each of the plurality of passphrases to a text-dependent or text-independent voice biometric model. The passphrase is transmitted to the customer, and when the customer responds, an audio stream of the passphrase is received. The customer is authenticated by comparing the audio stream of the passphrase against the text-independent voice print.

Abstract: In a system and method for audio analysis in a cloud-based computerized an authentication (RTA) manager micro-service may send an audio packet to a voice processor micro-service. The voice processor may extract features of the audio. The RTA manager may obtain the extracted features from the voice processor; calculate, based on the extracted features, a quality grade of the audio packet, and send the extracted features to an at least one voice biometrics engine if the quality grade is above a threshold. Each of the at least one voice biometrics engines may be configured to generate a voiceprint of the audio packet, based on the extracted features of the audio packet and to perform at least one of: authenticate a speaker, detect fraudsters, and enrich a previously stored voiceprint of the speaker with the voiceprint of the audio packet.

Abstract: A computerized-method for calculating an After-Call-Work (ACW) factor of an interaction in a contact center, by which a related recording may be filtered for evaluation is provided herein. The method includes an After-Call-Work (ACW) factor calculation module. The operating of the ACW factor calculation module includes: (i) receiving agent recording of the interaction. (ii) aggregating data fields associated with: (a) the interaction; and (b) the customer; (iii) retrieving ACW time of the interaction; (iv) forwarding the aggregated data fields to a machine learning model; (v) operating the machine learning model to calculate a predicted ACW time, based on the aggregated data fields; (vi) calculating an ACW factor based on the received time of ACW and the calculated predicted ACW time; and (vii) sending the calculated ACW factor to a platform by which the platform is preconfigured to distribute the interaction for evaluation, based on the ACW factor.

Abstract: A system and method for creating input data to be used to train a conversational bot may include receiving a set of conversations, each conversation including sentences, classifying each sentence into a dialog act taken from a number of dialog acts, for each set of sentences classified into a dialog act, clustering the set of sentences into clusters based on the content (e.g. text) of the sentences, each cluster having a cluster name or label, and generating a language model based on the cluster labels. Slots may be identified in the sentences based in part on the dialog act classifications. A bot may be trained using data such as the slots, language model, and clusters.

Abstract: A method and system for analyzing interactions (for example between a person and an organization) may include for a number of series of interactions (which may be termed journeys), each interaction represented by a channel and a reason, iterating over the series of interactions by selecting initial information including an interaction subset including one or more interactions, and if there is a set of interaction series among the series of interactions meeting certain conditions, adding an interaction to the interaction subset and determining in a recursive fashion if for the interaction subset, there is a subset among the set of interaction series meeting the conditions which also meet the conditions. Conditions may include a threshold average rating for the set of interaction series, and a threshold number of interaction series in which the interaction subset is found.

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 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 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: A system and methods are provided for a workforce management (WFM) system adapted to perform automated scheduling operations based on scheduling rule(s) and/or parameter(s). The system includes a processor and a computer readable medium operably coupled thereto, to perform the scheduling operations which include automatically generating a survey comprising queries based on the scheduling rule(s) and parameter(s) having at least a first and second dimension, distributing the survey to user(s) via one or more interfaces of the WFM system, detecting each response to the survey via the WFM system, analyzing, using a deep learning model, each survey response, generating one or more recommendations for the user(s) based on analyzing each response using the deep learning model, detecting one or more feedbacks to the survey via the WFM system, and adjusting, using the deep learning model and the feedback(s) to the recommendation(s), one or more of the parameters for the survey.

Abstract: A method for separating and authenticating speech of a speaker on an audio stream of speakers over an audio channel may include receiving audio stream data of the audio stream with speech from a speaker to be authenticated speaking with a second speaker. A voiceprint may be generated for each data chunk in the audio stream data divided into a plurality of data chunks. The voiceprint for each data chunk may be assessed as to whether the voiceprint has speech belonging to the speaker to be authenticated or to the second speaker using representative voiceprints of both speakers. An accumulated voiceprint may be generated using the verified data chunks with speech of the speaker to be authenticated. The accumulated voiceprint may be compared to the reference voiceprint of the speaker to be authenticated for authenticating the speaker speaking with the second speaker over the audio channel.

Abstract: A system and method for detecting and fixing robotic process automation failures, including collecting tasks from at least one client computerized device, processing the tasks via robotic process automation, collecting tasks that failed to complete per task type, recording successful execution steps per each of the failed tasks, evaluating the recorded successful execution steps with respect to the failed task types, and providing selected execution steps that best fix the failed tasks, thereby fixing the robotic process automation failures.

Abstract: A computerized-method for providing real-time lockless parallel screen recording compliance enforcement to omni-channel cloud systems, is provided herein. In a processor of a client computer configured to execute code for recording events of one or more voice or digital interactions, on one or more screens associated to the client computer, the computerized-method maintains a cache for storing a masked state. Each interaction is having an associated interaction identifier and upon receiving a screen event from a server of a cloud-based video recording that is communicating with the client computer over a communication network, operating a compliance-enforcement module. The compliance-enforcement module includes updating the cache; and operating a module of recording of screen events for the screen events of the one or more voice or digital interactions. Thus, by updating in real-time the cache on the client computer refraining from database locks in the server of the cloud-based video recording.