Abstract: A system and method for emotion-enhanced natural speech using dilated convolutional neural networks, wherein an audio processing server receives a raw audio waveform from a dilated convolutional artificial neural network, associates text-based emotion content markers with portions of the raw audio waveform to produce an emotion-enhanced audio waveform, and provides the emotion-enhanced audio waveform to the dilated convolutional artificial neural network for use as a new input data set.

Abstract: A system and method for customer interaction and experience enhancement which automatically gathers direct and indirect customer communications about products and services, converts them to text where necessary, and analyzes the communications for sentiment and emotional content, and scores and displays the information in a manner conducive to making business decisions based on the customer sentiment and emotion, such as making changes to products or services, troubleshooting customer service interactions, and better marketing.

Abstract: A system and method for improved categorization and sentiment analysis which is fed textual data such as transcriptions or collated data from a network enabled service, or some other source, which then segments textual data into chunks, parses the data chunks, and analyzes it using a plurality of techniques and metadata gathering methods to determine the sentiment of participating individuals concerning entities mentioned in the textual data and to categorize the discussions, for the purpose of taking actions to improve business outcomes.

Abstract: A system for automatically automatic workflow triggering using real-time analytics, comprising an analytics server that receives and analyzes interaction information and a workflow server that produces workflow events based on the analysis, sends workflow events to handlers for processing, retrieves workflow-related data, and produces workflow reports for review, and a method for automatically automatic workflow triggering using real-time analytics.

Abstract: A system and method for an optimized, self-learning and self-organizing contact center has been developed. This system and method uses principles and tools of information theory, including the latent Dirichlet allocation which reduces information to specific predetermined topics and a distribution of topic related words to infer its hidden, generative underpinnings so to self-organize a contact center, infer its desired electronic versus human make up, and optimally route all customer requests to an electronic resource or a specific human agent best suited to respond to the request for maximal business value per interaction.

Abstract: A system and method for emotion-enhanced natural speech using dilated convolutional neural networks, wherein an audio processing server receives a raw audio waveform from a dilated convolutional artificial neural network, associates text-based emotion content markers with portions of the raw audio waveform to produce an emotion-enhanced audio waveform, and provides the emotion-enhanced audio waveform to the dilated convolutional artificial neural network for use as a new input data set.

Abstract: A system for automatically automatic workflow triggering using real-time analytics, comprising an analytics server that receives and analyzes interaction information and a workflow server that produces workflow events based on the analysis, sends workflow events to handlers for processing, retrieves workflow-related data, and produces workflow reports for review, and a method for automatically automatic workflow triggering using real-time analytics.

Abstract: A system and method for improved categorization and sentiment analysis which is fed textual data such as transcriptions or collated data from a network enabled service, or some other source, which then segments textual data into chunks, parses the data chunks, and analyzes it using a plurality of techniques and metadata gathering methods to determine the sentiment of participating individuals concerning entities mentioned in the textual data and to categorize the discussions, for the purpose of taking actions to improve business outcomes.

Abstract: A system and method for an optimized, self-learning and self-organizing contact center has been developed. This system and method uses principles and tools of information theory, including the latent Dirichlet allocation which reduces information to specific predetermined topics and a distribution of topic related words to infer its hidden, generative underpinnings so to self-organize a contact center, infer its desired electronic versus human make up, and optimally route all customer requests to an electronic resource or a specific human agent best suited to respond to the request for maximal business value per interaction.

Abstract: A system and method for customer interaction and experience enhancement which automatically gathers direct and indirect customer communications about products and services, converts them to text where necessary, and analyzes the communications for sentiment and emotional content, and scores and displays the information in a manner conducive to making business decisions based on the customer sentiment and emotion, such as making changes to products or services, troubleshooting customer service interactions, and better marketing.

Abstract: A system and method for an optimized, self-learning and self-organizing contact center has been developed. This system and method uses principles and tools of information theory, including the latent Dirichlet allocation which reduces information to specific predetermined topics and a distribution of topic related words to infer its hidden, generative underpinnings so to self-organize a contact center, infer its desired electronic versus human make up, and optimally route all customer requests to an electronic resource or a specific human agent best suited to respond to the request for maximal business value per interaction.

Abstract: A system and method for improved categorization and sentiment analysis which is fed textual data such as transcriptions or collated data from a network enabled service, or some other source, which then segments textual data into chunks, parses the data chunks, and analyzes it using a plurality of techniques and metadata gathering methods to determine the sentiment of participating individuals concerning entities mentioned in the textual data and to categorize the discussions, for the purpose of taking actions to improve business outcomes.

Abstract: Briefly, embodiments disclosed herein may relate to re-physicalization of captured physical signals and/or sensor measurements and to generation of user-perceivable output content from a computing device based at least in part on the re-physicalization.

Abstract: A system and method for improved categorization and sentiment analysis which is fed textual data such as transcriptions or collated data from a network enabled service, or some other source, which then segments textual data into chunks, parses the data chunks, and analyzes it using a plurality of techniques and metadata gathering methods to determine the sentiment of participating individuals concerning entities mentioned in the textual data and to categorize the discussions, for the purpose of taking actions to improve business outcomes.

Abstract: A system and method for customer interaction and experience enhancement which automatically gathers direct and indirect customer communications about products and services, converts them to text where necessary, and analyzes the communications for sentiment and emotional content, and scores and displays the information in a manner conducive to making business decisions based on the customer sentiment and emotion, such as making changes to products or services, troubleshooting customer service interactions, and better marketing.

Abstract: A system and method for customer interaction and experience enhancement which automatically gathers direct and indirect customer communications about products and services, converts them to text where necessary, and analyzes the communications for sentiment and emotional content, and scores and displays the information in a manner conducive to making business decisions based on the customer sentiment and emotion, such as making changes to products or services, troubleshooting customer service interactions, and better marketing.

Abstract: A system for using conversational similarity for dimension reduction in deep analytics, comprising a self-learning interaction optimizer that receives string-based data from a contact center and analyzes it to produce a plurality of information similarity vectors, provides the vectors to a neural network and receives output vectors from the neural network, and produces context data from the output vectors and associates the context data with the original string-based data.

Abstract: A system for using conversational similarity for dimension reduction in deep analytics, comprising a self-learning interaction optimizer that receives string-based data from a contact center and analyzes it to produce a plurality of information similarity vectors, provides the vectors to a neural network and receives output vectors from the neural network, and produces context data from the output vectors and associates the context data with the original string-based data.

Abstract: A system for automatically automatic workflow triggering using real-time analytics, comprising an analytics server that receives and analyzes interaction information and a workflow server that produces workflow events based on the analysis, sends workflow events to handlers for processing, retrieves workflow-related data, and produces workflow reports for review, and a method for automatically automatic workflow triggering using real-time analytics.

Abstract: A system and method for enhanced human/machine workforce management using reinforcement learning, comprising a reinforcement learning server that produces a partially-observable Markov chain model, and an optimization server that uses the partially-observable Markov chain model to select work items and assign them to contact center resources.