Abstract: Systems and methods include using a clustering engine to determine topics in a communication. An example system includes a user interface module that receives user input relating to a criteria to define a set of communications, wherein the criteria is at least one of a category, a score, a sentiment, an agent, an agent grouping, a speaker, a location, an event attribute, a call center, a time of communication, or a date of communication, an acoustic analysis module that analyzes the set of communications to determine one or more acoustic characteristics of one or more communications in the set of communications, and a clustering engine that analyzes words and phrases in the set of communications and the one or more acoustic characteristics, and to determine a topic of the set of communications based on at least one commonality in words, phrases, or the one or more acoustic characteristics.

Abstract: Systems and methods include identifying sets of communications using AB testing based on a difference in metadata values between the sets for a first type of metadata, determining at least one similarity between communications in a first set based on metadata values of a second type of metadata, determining at least one similarity between the communications in the second set based on metadata values of the second type of metadata or a third type of metadata, comparing the at least one similarity from the first set to the at least one similarity of the second set to identify differences in metadata values or types of metadata, and determining, based on the differences, a suggested action for an agent for a future communication with respect to at least one of a desired script, a target phrase, or a desired acoustic characteristic.

Abstract: Systems and methods for searching communications may include receiving a selection from a user of at least one of an acoustic characteristic, a language characteristic, or a category, accessing a database comprising a plurality of communications, the plurality of communications labeled with acoustic characteristics, language characteristics, and categories, restricting the plurality of communications to a subset of the plurality of communications including the user's selection of the at least one acoustic characteristic, language characteristic, or category, generating at least one of a word cloud or a tree for presenting a plurality of topics identified in the subset of the plurality of communications, and receiving a selection of one of the plurality of topics, the receiving causing a display of a further subset of the subset of the plurality of communications, the further subset having the selected topic.

Abstract: Systems and methods include identifying sets of communications using AB testing based on a difference in metadata values between the sets for a first type of metadata, determining at least one similarity between communications in a first set based on metadata values of a second type of metadata, determining at least one similarity between the communications in the second set based on metadata values of the second type of metadata or a third type of metadata, comparing the at least one similarity from the first set to the at least one similarity of the second set to identify differences in metadata values or types of metadata, and determining, based on the differences, a suggested action for an agent for a future communication with respect to at least one of a desired script, a target phrase, or a desired acoustic characteristic.

Abstract: Content, such as communications, can be searched by their acoustic characteristics, among others. A method may include analyzing a plurality of content for at least one of a language characteristic or a non-word symbol within a text of the plurality of content, and an acoustic characteristic, searching the plurality of content using a search string comprising at least one of a language characteristic, or a non-word symbol, and an acoustic characteristic, and presenting a subset of the plurality of content ranked according to a match with the search string. In some cases, a category label is determined for the content and is also used in the search string.

Abstract: A system and method of categorizing communications involves evaluating one or more portions of a communication. Systems include a language module structured to analyze the one or more portions of the communication for at least one of a language characteristic or a non-word symbol within a text of the communication, an acoustic analysis module structured to analyze the one or more portions of the communication for an acoustic characteristic, and a determination module structured to determine at least one category label to associate with the one or more portions of the communication using at least one of the language characteristic or the non-word symbol, and the acoustic characteristic.

Abstract: A contact center agent coaching tool may employ systems and methods comprising receiving a communication involving a participant, analyzing the communication in at least near real-time relative to a receipt of the communication using a computer-based communications analytics facility for at least one of a language characteristic, a non-word symbol, or an acoustic characteristic, analyzing the communication in at least near real-time relative to the receipt of the communication using a contextual analysis to obtain a context, determining at least one of a category or a score associated with an aspect of the communication using the at least one language characteristic, non-word symbol, acoustic characteristic, or the context, and triggering a coaching tool to be presented to the participant based on at least one of the category or the score.

Abstract: A communication channel customer journey may involve receiving a first communication on a communication channel of a plurality of communication channels, wherein the first communication is associated with a contact, receiving at least one additional communication from the contact, wherein the at least one additional communication is on a same communication channel or is on a different communication channel of the plurality of communication channels, linking the first communication and the at least one additional communication by the contact, wherein linking involves storing information from at least one of a recording, a transcript, a copy of one or more of the first communication and the at least one additional communication, a language characteristic, an acoustic characteristic, a category, and a score, and enabling a user to navigate between all of the stored information for the first communication and the at least one additional communication.

Abstract: Disclosed herein is a system that provides analysis of language or acoustic characteristics of a communication including a receiver and a computer-based communications analytics facility including at least one of: a language analysis module for analyzing the communication for at least one of a language characteristic and a non-word symbol within the communication text that connotes a verbal element, an acoustic analysis module for analyzing the communication for an acoustic characteristic, and a contextual module for analyzing a context of words within the communication. The system also includes a determination module for determining an alert associated with the communication using at least one of the language characteristic, the non-word symbol, the acoustic characteristic, and the context, wherein the alert concerns a presence or an absence of specific language; and an interface for displaying at least one visual, textual, or numerical indication representative of the alert.

Abstract: Methods and systems are provided for receiving a communication, analyzing the communication in real-time or near real-time using a computer-based communications analytics facility for at least one of a language characteristic and an acoustic characteristic, wherein for analyzing the language characteristic of voice communications, the communication is converted to text using computer-based speech recognition, determining at least one of the category, the score, the sentiment, or the alert associated with the communication using the at least one language and/or acoustic characteristic, and providing a dynamic graphical representation of the at least one category, score, sentiment, or alert through a graphical user interface.

Abstract: Computer-implemented methods and apparatus are provided to facilitate the recognition of the content of a body of speech data. In one embodiment, a method for analyzing verbal communication is provided, comprising acts of producing an electronic recording of a plurality of spoken words; processing the electronic recording to identify a plurality of word alternatives for each of the spoken words, each of the plurality of word alternatives being identified by comparing a portion of the electronic recording with a lexicon, and each of the plurality of word alternatives being assigned a probability of correctly identifying a spoken word; loading the word alternatives and the probabilities to a database for subsequent analysis; and examining the word alternatives and the probabilities to determine at least one characteristic of the plurality of spoken words.

Abstract: Computer-implemented methods and apparatus are provided to facilitate the recognition of the content of a body of speech data. In one embodiment, a method for analyzing verbal communication is provided, comprising acts of producing an electronic recording of a plurality of spoken words; processing the electronic recording to identify a plurality of word alternatives for each of the spoken words, each of the plurality of word alternatives being identified by comparing a portion of the electronic recording with a lexicon, and each of the plurality of word alternatives being assigned a probability of correctly identifying a spoken word; loading the word alternatives and the probabilities to a database for subsequent analysis; and examining the word alternatives and the probabilities to determine at least one characteristic of the plurality of spoken words.

Abstract: Computer-implemented methods and apparatus are provided to facilitate the recognition of the content of a body of speech data. In one embodiment, a method for analyzing verbal communication is provided, comprising acts of producing an electronic recording of a plurality of spoken words; processing the electronic recording to identify a plurality of word alternatives for each of the spoken words, each of the plurality of word alternatives being identified by comparing a portion of the electronic recording with a lexicon, and each of the plurality of word alternatives being assigned a probability of correctly identifying a spoken word; loading the word alternatives and the probabilities to a database for subsequent analysis; and examining the word alternatives and the probabilities to determine at least one characteristic of the plurality of spoken words.

Abstract: Methods and apparatus are provided which may be employed to perform speech recognition processing on a grid computing system. In some embodiments, the grid computing system includes a server system which receives processing tasks from one or more client applications, divides the processing tasks into units of work, and assigns the units of work to one or more of the nodes. Dividing a processing task into units of work may involve dividing audio input data into segments defined by natural speech boundaries. A mathematical representation may be created for each segment prior to its distribution on the grid to minimize network traffic. A node in the system may perform heterogeneous units of work concurrently, such as by isolating the execution of each unit of work in an application domain.

Abstract: Methods and apparatus are provided which may be employed to perform speech recognition processing on a grid computing system. In some embodiments, the grid computing system includes a server system which receives processing tasks from one or more client applications, divides the processing tasks into units of work, and assigns the units of work to one or more of the nodes. Dividing a processing task into units of work may involve dividing audio input data into segments defined by natural speech boundaries. A mathematical representation may be created for each segment prior to its distribution on the grid to minimize network traffic. A node in the system may perform heterogeneous units of work concurrently, such as by isolating the execution of each unit of work in an application domain.

Abstract: Methods and apparatus are provided which may be employed to perform speech recognition processing on a grid computing system. In some embodiments, the grid computing system includes a server system which receives processing tasks from one or more client applications, divides the processing tasks into units of work, and assigns the units of work to one or more of the nodes. Dividing a processing task into units of work may involve dividing audio input data into segments defined by natural speech boundaries. A mathematical representation may be created for each segment prior to its distribution on the grid to minimize network traffic. A node in the system may perform heterogeneous units of work concurrently, such as by isolating the execution of each unit of work in an application domain.