Abstract: A computerized system and method may process and predict stress levels for audio data using a machine learning based framework. A computerized system including a processor and a memory may calculate a buffer length based on a plurality of audio attributes (e.g., of a given audio input or data item), extract an audio buffer from an audio data item based on the calculated length, and predict, using a machine learning model, a stress level for the audio buffer or data item. Some embodiments of the invention may include extracting a buffer of a length determined dynamically for different audio inputs, e.g., to ensure coherency between audio attributes or features extracted from different audio inputs having different audio characteristics. In some embodiments, audio features which may be considered by the model may include, e.g., a plurality of gradients between mel-frequency cepstrum coefficients computed for relevant audio buffers or inputs.

Abstract: Coaching systems and methods, and non-transitory computer readable media, include analyzing an agent's interactions to identify knowledge gaps and specific topics where an agent has difficulties. An algorithm uses bootstrap sampling to verify that an agent's scores are significantly different from other agents' scores. The algorithm further uses a mutual information score to find topics that are associated with interactions having a high knowledge gap score.

Abstract: A computerized system and method may automatically generate a hierarchical, multi-tiered taxonomy based on measuring and/or quantifying degrees of generality for a plurality of input entities. In some embodiments of the invention, a computerized system comprising a processor, and a memory including a plurality of entities such as documents or text files, may be used for extracting words from a plurality of documents; calculating generality scores for the extracted words; selecting some of the extracted words as exemplars based on the scores; and clustering unselected words under appropriate exemplars to produce or output a corresponding taxonomy. Some embodiments of the invention may allow categorizing interactions among remotely connected computers using a domain taxonomy, and routing interactions between remotely connected computer systems based on the taxonomy.

Abstract: A system is provided for an automation tool system that is adapted to analyze data structures for robotic process automation (RPA) solutions. The system includes a processor and a computer readable medium operably coupled thereto, to perform operations which include receiving a data structure for an automated computing task for the RPA solutions of a computing system, wherein the data structure comprises one or more computing assets for one or more data processing workflows, parsing the data structure, accessing rule scoring parameters for determining a set of best practices identified for construction of the automated computing task for the RPA solutions of the computing system, scoring the automated computing task for the RPA solutions for the computing system based on the parsing and the rule scoring parameters, and outputting, based on scoring the automated computing task, a score of the automated computing task for the data structure.

Abstract: Systems and methods for automatic real-time monitoring of interactions, carried out by at least one computer processor, including: producing a score for each text component of a text representation of an interaction; producing, based on the score for each text component, a score for each of a plurality of time periods of the interaction; producing a score history, including a plurality of the time period scores; and calculating, based on the score history, a real-time indication of the quality of the interaction.

Abstract: Systems and methods for mapping a set of output values of a first learning model to a distribution of a set of output values of a second learning model include: calculating a distribution function for a set of source values; calculating a distribution function for a set of target values; calculating a set of quantiles for each distribution function; using the set of quantiles in a linear interpolation of the set of target values to obtain a source values array and a matched interpolated values array; calculating an absolute distance from each value in the source values array to the first set of output values of the first learning model; determining a corresponding value in the matched interpolated values array corresponding to a value in the source values array which has the smallest said absolute distance; and outputting a set of matched values.

Abstract: A computerized-method for sensitive data redaction from screenshots, is provided herein. The computerized-method includes retrieving records of a sequence of screenshots from a database. Then, grouping the sequence-of-screenshots by one feature of one or more features to yield one or more groups. Each group includes screenshots having one common feature. Then, calculating a score for each pixel across all similar screenshots in each group. For each group of screenshots, blackening pixels in all screenshots having a score above a preconfigured threshold to yield data redacted screenshots. The score of each pixel above the preconfigured threshold indicates a high variance between screenshots in the group and a presence of sensitive data therein and then storing the data-redacted screenshots in a screenshots-database.

Abstract: A system to create new automation routines includes a processor to: Over time, store a group of actions taken by a group of agents within applications. From the stored group of actions, identify a repeating pattern of actions in a subset of the applications, and construct a binary vector, each position within the binary vector storing a 1 for an occurrence of any action within any application of the subset, and a 0 otherwise. From the binary vector and the repeating pattern, extract a sentence including at least one action within at least one application. Based on the repeating pattern, an application type, or a business goal, create a constraint. If the sentence meets the constraint, accept the sentence and add it to a pool of accepted sentences. From the pool of accepted sentences, identify a pattern of occurrences of the accepted sentence, and create a new automation routine.

Abstract: A system and method for determining an embedding for a document (e.g. representing the document in vector space) by determining for the document a preliminary document embedding; determining for the document a document topic embedding based on a set of nearest topics to the preliminary document embedding; determining for each phrase in the document a topic relevancy score based on the document topic embedding and the embedding associated with the phrase; using a ranking algorithm to determine a saliency score for each phrase in the document, each saliency score based on the topic relevancy score for the phrase, and an inverse frequency score for the phrase; and calculating an embedding for the document using the saliency scores and embedding, for the phrases in the document.

Abstract: A computer based system and method for measuring effectiveness of a gamification challenge may include: presenting the gamification challenge on a display to an agent; measuring agent engagement with the gamification challenge over time to calculate agent engagement indices over time; measuring agent performance over time to calculate agent performance indices over time; and calculating a correlation between the agent engagement indices and the agent performance indices to obtain the gamification effectiveness.

Abstract: A transaction tracking system includes a display that permits viewing the relationship between related transactions. In the display, individual transactions are depicted as transaction icons sorted in time order horizontal rows according to order ID.

Abstract: A system and method for authenticating an identity may include generating a first generic representation representing a stored audio content, generating a second generic representation representing input audio content, and, providing the first and second generic representations to a voice biometrics unit adapted to authenticate an identity based on the first and second generic representations.

Abstract: A computerized-method for recommending activities for an agent, in a contact center is provided herein. The computerized-method includes operating an activities-recommendation module, for agents in a contact center, during a work-shift of an agent.

Abstract: A method and system may select an interaction involving an agent, sending the selected interaction and a computerized form to the agent and an evaluator, simultaneously or concurrently, displaying to the evaluator and agent screens defined by the form, each screen including an evaluation question, accepting from the agent, for each evaluation question, an agent answer having associated with the agent answer a rating, accepting from the evaluator a submission indicating that the evaluator has completed the computerized evaluation form, accepting from the agent a submission indicating that the agent has completed the computerized evaluation form, summing an agent rating from the ratings associated with the agent answers provided by the agent, summing an evaluator rating from the ratings associated with evaluator answers provided by the evaluator, and calculating a variance from the agent rating and evaluator rating.

Abstract: Moist wipes having improved dispersibility are provided. The moist wipes are sufficiently strong during use and disperse sufficiently quickly under real world conditions to be flushable without creating potential problems for sanitation systems.

Abstract: A method and system for evaluating bot performance, including collecting, by a processor, bot performance data items, wherein the collecting includes directly collecting bot performance data items; and calculating bot performance data items based on collected bot performance metrics; producing a bot performance output including bot performance data items; and assessing the bot performance output. Assessment of the bot performance output may initiate bot quality management, wherein the bot quality management includes, assessing the bot update recommendations. Assessment of the bot update recommendations may result in initiating bot update.

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: A system is provided for real-time fraud detection with a fraudster voice print watchlist of repetitive fraudster phrases. The system includes a processor and a computer readable medium operably coupled thereto, to perform fraud prevention operations which include detecting a voice communication session having an audio signal of a user, accessing the fraudster voice print watchlist comprising a plurality of fraudster voice prints of the repetitive fraudster phrases, generating a voice print of the user using the audio signal, monitoring the user for real-time fraud detection using the fraudster voice print watchlist and the voice print of the user, and determining, based on the monitoring, whether the voice print of the user meets or exceeds a scoring threshold for matching with one or more of the plurality of fraudster voice prints from the fraudster voice print watchlist during the voice communication session.

Abstract: A system and method for training and using a text embedding model may include creating structured phrases from an input text; creating turn input samples from the input text, each turn input sample based on only or consisting of input from a single turn within the text and being formed by removing structure from structured phrases; and training an embedding model using the structured phrases and turn input samples. Call input samples may be created based on input from more than one turn within the text. At each level of resolution (e.g. phrase, speaker, call), a different level of resolution may be used to create input samples. At inference an embedding may be based on a weighted combination of the sub-terms within an input phrase, each weight being based on an inverse document frequency measure for the sub-term associated with the weight.

Abstract: A method and a system for revising a score associated with interaction feedback, wherein the method may include: traversing a score revision decision tree to categorize the interaction, based on interaction data and interaction feedback data associated with the interaction; and selecting, based on the categorization of the interaction, an indication of a probability that the score associated with the interaction feedback should be revised; wherein interaction data may include data extracted from the interaction; interaction feedback data may include data extracted from feedback about the interaction; and the score revision decision tree may include a decision tree data structure including at least one decision node, each decision node including to at least one data point of the interaction data or interaction feedback data.