Abstract: A method comprising: receiving a first text corpus comprising punctuated and capitalized text; annotating words in said first text corpus with a set of labels indicating a punctuation and a capitalization of each word; at an initial training stage, training a machine learning model on a first training set comprising: (i) said annotated words in said first text corpus, and (ii) said labels; receiving a second text corpus representing conversational speech; annotating words in said second text corpus with said set of labels; at a re-training stage, re-training said machine learning model on a second training set comprising: (iii) said annotated words in said second text corpus, and (iv) said labels; and at an inference stage, applying said trained machine learning model to a target set of words representing conversational speech, to predict a punctuation and capitalization of each word in said target set.

Abstract: A system and method for multimedia contact center interactions via an audiovisual asynchronous messaging channel is provided. In an embodiment, an organization might operate a website comprising information and for providing an entry point of communication with a contact center. A communications channel may be integrated directly with the organization's website, which includes an editable audiovisual interface. A user may interact with the editable interface through a variety of means, including sketching on a webpage and recording to create a video form of audiovisual asynchronous query over the web page. The interaction is analyzed and routed to an agent for handling. The agent may then be connected to the user through the asynchronous channel.

Abstract: A method for conducting an automated interview session between a candidate and an automated chat resource includes analyzing a candidate resume to identify a first personality trait; generating a first resume-based question based on the first personality trait; presenting, by the automated chat resource, the first resume-based question to the candidate during the automated interview session based on the identified first personality trait; generating a first trait score based on a first response received from the candidate, wherein the first trait score is indicative of a relevance of the identified first personality trait; generating a first question-answer score based on the first resume-based question and the first response, wherein the first question-answer score is indicative of a first question-answer relevance and is used to determine whether to present a second resume-based question to the candidate; analyzing a communication transcript to identify a second personality trait; generating a first transcr

Abstract: A system including a mobile application on a user's mobile device for connecting to a plurality of contact centers and providing personalized context to the user. The system includes: the mobile application; a connection from the mobile application to a central API service, wherein the central API service provides authentication tokens to the mobile application for facilitating interaction therebetween; a plurality of vendors which the user has associated with their profile and have been integrated with the central API service, wherein the vendors are operably connected with the central API service for information sharing; and a plurality of media channels connecting the plurality of vendors with the central API service, allowing the user to: view personalized context from past interactions between the user and the plurality of contact centers through the mobile application; and connect with the contact centers.

Abstract: A method for authoring a conversational bot including: receiving conversation data; receiving seed intent data that comprises seed intents having a seed intent label and sample intent-bearing utterances; using an intent mining algorithm to mine the conversation data to determine new utterances to associate with the seed intent; augmenting the seed intent data to include the mined new utterances associated with the seed intents; and uploading the augmented seed intent data into the conversation bot. The intent mining algorithm may include: identifying intent-bearing utterances; identifying candidate intents; for each of the seed intents, identifying seed intent alternatives from the sample intent-bearing utterances; associating the intent-bearing utterances from the conversation data with the seed intents via determining a degree of semantic similarity between the candidate intents of the intent-bearing utterances and the seed intent alternatives.

Abstract: A method for intent mining that includes: receiving conversation data; using an intent mining algorithm to automatically mine intents from the conversation data; and uploading the mined intents into the conversational bot. The intent mining algorithm may include: analyzing utterances of the conversation data to identify intent-bearing utterances; analyzing the identified intent-bearing utterances to identify candidate intents; selecting salient intents from the candidate intents; grouping the selected salient intents into salient intent groups in accordance with a degree of semantic similarity; for each of the salient intent groups, selecting one of the salient intents as the intent label and designating the others as the intent alternatives; and associating the intent-bearing utterances with the salient intent groups via determining a degree of semantic similarity between the candidate intents present in the intent-bearing utterance and the intent alternatives within each group.

Abstract: A method for optimizing a workflow of deferrable work interactions in a contact center that includes: providing a NLP models and a priority model; using text derived from received deferrable working interactions as inputs to the NLP models to generate the NLP scores; using the LP scores as inputs to the priority model to generate the priority score; identifying candidate agents of the agents for handling the deferrable work interactions; receiving an inbound work forecast; receiving agent work schedule data; using an optimization process to generate an optimized workflow for the deferrable work interactions, where the optimized workflow includes assignments in which an agent from the candidate agents is selected to handle the deferrable work interaction and a target timeframe for handling is scheduled; and routing the deferrable work interactions in accordance with the assignments of the optimized workflow.

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: 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: A method related to predicting agent attrition rate that includes: providing an attrition model; measuring and recording agent journey data of a first agent of a contact center, the agent journey data describing aspects related to an employment of the first agent and having data types that corresponds in kind to data types of inputs of the attrition model; determining that prediction of an attrition rate of the first agent is required; using the attrition model to predict the attrition rate by providing values for the inputs from applicable values taken from the agent journey data of the first agent, and calculating the attrition rate as the output of the attrition model; determining if the calculated current attrition rate indicates a high risk of attrition; and transmitting an alert communication to a supervisor of the first agent.

Abstract: A method facilitating a customer exercising post-purchase rights associated with a purchase made by the customer of a product. The method includes: receiving first documentation related to the purchase of the product; extracting purchase data from the first documentation, where the extracted purchase data describes the purchase including a vendor identify, purchase date, and product type; conducting search using terms derived from the extracted purchase data to connect to a vendor web site; conducting a search of the vendor web site using terms derived from the extracted purchase data to locate a first vendor policy of the vendor that defines a first post-purchase right of the customer; determining a milestone date associated with the first post-purchase right of the customer; and sending a notification to the customer appraising the customer of the milestone date and the material change.

Abstract: A method for incorporating an augmented voice communication into a communication routing configuration of a contact center system according to an embodiment includes selecting a vocal avatar, wherein the vocal avatar includes phonetic characteristics having first values, receiving a text communication and input user parameters from an input user, generating the augmented voice communication based on the text communication and the input user parameters, wherein the augmented voice communication includes phonetic characteristics having second values, wherein the first values of the phonetic characteristics of the vocal avatar are different from the second values of the phonetic characteristics of the augmented voice communication, and incorporating the augmented voice communication into the communication routing configuration of the contact center system.

Abstract: A method for selectively transcribing voice communications that includes: receiving keywords; receiving an audio stream of audio data of speech; searching the audio stream to detect keywords or keyword detections and recording parameter data for each that includes a location of the keyword within the audio stream; generating one or more cumulative datasets for one or more portions of the audio stream that each includes parameter data for the keyword detections occurring therein; for each of the one or more portions of the audio stream, calculating a transcription favorableness score via inputting the corresponding one of the one or more cumulative datasets into an algorithm; and determining whether to transcribe each of the one or more portions of the audio stream by comparing the corresponding transcription favorableness score against a predetermined threshold.

Abstract: A system and method are presented relating to emotion-based action recommendations. The present invention may include a recommender engine that analyzes several pieces of information and using artificial intelligence derived models, provides a course of action for a contact center agent and the probability and estimations behind the recommendation as a justification. System inputs include cost of the item or service being troubleshooted, estimated costs for different resolutions, cost of each escalation level of the interaction, history of previous interactions, agent costs, history of the current interaction, acoustic events and sentiment or primary detected emotions of the customer's transcript. The recommended course of action, rationale, and authorization can be provided as output. The system may record whether the agent followed the recommendation to improve further recommendations.

Abstract: A method related to customers orchestrating engagements with service providers. The method includes providing, by a facilitator entity, a customer journey orchestration service that includes: service providers affiliated with the customer journey orchestration service; a virtual datacenter in which cloud-based applications and databases are operably linked to communication devices of the customers and to the affiliated services providers; customer interface portals for enabling the customers to interact with the virtual datacenter, each customer interface portal being associated with a specific customer; and a customer profile database that stores customer profiles corresponding to respective ones of the customers. The method further includes configuring, by the facilitator entity, an account of the customer for participation in the customer journey orchestration service.

Abstract: A method for verifying an individual's identity for granting access to a computer system that includes receiving a personal identifier of the individual and data related to the individual speaking an authentication sequence. The method includes performing a biometrics identity proof that includes: identifying a first set of characteristics from the data; retrieving, from a database, a second set characteristics linked to the personal identifier of the individual; and comparing the first set of characteristics against the second set of characteristics to determine a similarity score. The method includes performing a proof of possession of an authentication device that includes determining whether a recognized value of the authentication sequence matches an expected value of the authentication sequence. The method includes calculating a confidence score for verifying the individual's identity based the similarity score and whether a match was determined.

Abstract: A method for automated generation of contact center system embeddings according to one embodiment includes determining, by a computing system, contact center system agents, contact center system agent skills, and/or contact center system virtual queue experiences; generating, by the computing system, a matrix representation based on the contact center system agents, the contact center system agent skills, and/or the contact center system virtual queue experiences; generating, by the computing system and based on the matrix representation, contact center system agent identifiers, contact center system agent skills identifiers, and/or contact center system virtual queue identifiers; transforming, by the computing system, the contact center system agent identifiers, the contact center system agent skills identifiers, and/or the contact center system virtual queue identifiers into the contact center system agent embeddings, contact center system agent skills embeddings, and/or contact center system virtual queue

Abstract: A system comprising: at least one hardware processor; and a non-transitory computer-readable storage medium having stored thereon program code, the program code executable by the at least one hardware processor to: receive, by a processor, data associated with an interaction between a customer and an agent in a contact center, automatically analyze, by the processor, said data to identify one or more topics associated with a content of said interaction, automatically associate, by the processor, one or more questions from a dataset of questions with each of said identified topics, automatically construct, by the processor, a questionnaire comprising said associated questions, and output said questionnaire to said customer.

Abstract: A system and method are presented for generating staffing requirements for deferred work in a contact center environment. In an embodiment, a simulation of deferred work performance is used to generate staffing requirement. Information, such as volume offered, expected handle time, available staff distributed throughout the intervals over a period of time, etc., are utilized for determining service performance metrics. The simulation accounts for transient data (e.g., number of deferred work handled or completed, number of backlog from an interval to the next, starting number of deferred work in the system, etc.) and determines performance metrics using that transient data.

Abstract: A computer-implemented method related to routing incoming interactions of contact centers. The method may include: receiving initial data identifying a first incoming interaction that includes information disclosing at least an intent of the first incoming interaction; and performing a first subprocess to generate a personalized routing profile tailored to facilitate routing the first incoming interaction in accordance with preferences of a first customer. The first subprocess may include: accessing data from a database, the database including at least a first customer profile storing data relating to the first customer; based on the accessed data and the intent of the first incoming interaction, determining preferred agent characteristics data of the first customer for the first incoming interaction; and generating the personalized routing profile so to include the preferred agent characteristics data of the first customer.