Abstract: Disclosed herein are systems and methods for redacting sensitive information. Certain methods involve caching an incoming communication in a cache of the machine, optionally, when the communication is a vocal stream, using a speech processor, converting the vocal stream to text before analyzing, and automatically analyzing the communication and identifying sensitive information in accordance with one or more rules and identifying the location of the sensitive information in the communication. The sensitive information is automatically redacted from the communication and the redacted communication is at least one of stored and transmitted.

Abstract: Disclosed herein are systems and methods for redacting sensitive information. Certain systems include a speech-to-text converter for converting a vocal stream to text, a text analysis module for automatically analyzing the text and identifying sensitive information in accordance with a plurality of rules, and identifying the location of the sensitive information in the vocal stream, and a multi-level redactor for redacting sensitive information from the vocal stream in accordance with the plurality of the rules.

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: 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.

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.