Abstract: A method of assisting an agent in real-time includes receiving a call interaction between a customer and an agent; identifying words spoken in the call interaction; providing the words to a behavioral models module; computing a score for a plurality of behavioral metrics; providing a phrase formed by the words to a knowledge article selection module; providing each score for the plurality of behavioral metrics to the knowledge article selection module; providing a plurality of knowledge selection rules to the knowledge article selection module; evaluating a combination of the phrase and the scores of the plurality of behavioral metrics against each of the plurality of knowledge selection rules; matching a knowledge selection rule to the combination; selecting a knowledge article associated with the matched knowledge selection rule; generating a visual representation of the selected knowledge article; and presenting in real-time the visual representation on a graphical user interface.

Abstract: A method of assisting an agent in real-time includes receiving a call interaction between a customer and an agent; identifying words spoken in the call interaction; providing the words to a behavioral models module; computing a score for a plurality of behavioral metrics; providing a phrase formed by the words to a knowledge article selection module; providing each score for the plurality of behavioral metrics to the knowledge article selection module; providing a plurality of knowledge selection rules to the knowledge article selection module; evaluating a combination of the phrase and the scores of the plurality of behavioral metrics against each of the plurality of knowledge selection rules; matching a knowledge selection rule to the combination; selecting a knowledge article associated with the matched knowledge selection rule; generating a visual representation of the selected knowledge article; and presenting in real-time the visual representation on a graphical user interface.

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: Methods for detecting fraud include receiving a plurality of call interactions; extracting a voice print of a caller from each of the call interactions; determining which call interactions are associated with a single caller by comparing and matching pairs of voice prints of the call interactions; organizing the call interactions associated with a single caller into a group; and determining that a matching phrase was spoken by the single caller in a first call interaction and second call interaction in the group.

Abstract: A method of assisting an agent in real-time includes receiving a call interaction between a customer and an agent; identifying words spoken in the call interaction; providing the words to a behavioral models module; computing a score for a plurality of behavioral metrics; providing a phrase formed by the words to a knowledge article selection module; providing each score for the plurality of behavioral metrics to the knowledge article selection module; providing a plurality of knowledge selection rules to the knowledge article selection module; evaluating a combination of the phrase and the scores of the plurality of behavioral metrics against each of the plurality of knowledge selection rules; matching a knowledge selection rule to the combination; selecting a knowledge article associated with the matched knowledge selection rule; generating a visual representation of the selected knowledge article; and presenting in real-time the visual representation on a graphical user interface.

Abstract: A method of assisting an agent in real-time includes includes receiving a call interaction between a customer and an agent; identifying words spoken in the call interaction; providing the words to a behavioral models module; computing a score for a plurality of behavioral metrics; providing a phrase formed by the words to a knowledge article selection module; providing each score for the plurality of behavioral metrics to the knowledge article selection module; providing a plurality of knowledge selection rules to the knowledge article selection module; evaluating a combination of the phrase and the scores of the plurality of behavioral metrics against each of the plurality of knowledge selection rules; matching a knowledge selection rule to the combination; selecting a knowledge article associated with the matched knowledge selection rule; generating a visual representation of the selected knowledge article; and presenting in real-time the visual representation on a graphical user interface.

Abstract: A system and method of voice authentication of an audio stream represented to be the spoken voice of a person, may include receiving via a device such as telephony device a voice stream or voice recording represented to be that of a person speaking, providing an interfering or interrupting audio signal to the device, and using information regarding the interfering audio signal, determining if the voice stream indicates a reaction to the audio output. In such a manner it may be determined if the spoken voice is that of a real, live, person, speaking in real-time, or that of a device or person attempting to imitate a person (e.g. using a recording).

Abstract: Systems and methods for optimizing matched voice biometric passphrases may generate a set of k candidate passphrases; calculate a phonetic content of each candidate passphrase of the set of k candidate passphrases; at least one of during and after a voice biometric enrollment of a user, calculate a user phonetic content of a text-independent voiceprint of the user, wherein the text-independent voiceprint of the user was captured during the voice biometric enrollment; identify a subset of j passphrases from the set of k candidate passphrases, wherein each of the subset of j passphrases meets a match threshold in phonetic content with the voiceprint of the user; one of prior to and during a user authentication, select a first one of the subset of j passphrases; and present the selected first one of the subset of j passphrases to the user for use in the user authentication.

Abstract: Systems and methods for optimizing matched voice biometric passphrases may generate a set of k candidate passphrases; calculate a phonetic content of each candidate passphrase of the set of k candidate passphrases; at least one of during and after a voice biometric enrollment of a user, calculate a user phonetic content of a text-independent voiceprint of the user, wherein the text-independent voiceprint of the user was captured during the voice biometric enrollment; identify a subset of j passphrases from the set of k candidate passphrases, wherein each of the subset of j passphrases meets a match threshold in phonetic content with the voiceprint of the user; one of prior to and during a user authentication, select a first one of the subset of j passphrases; and present the selected first one of the subset of j passphrases to the user for use in the user authentication.

Abstract: A method for analysis of a set of media recordings includes, in a first processing stage, selecting a subset of the set of media recordings by performing a first processing of each media recording of the set of media recordings and in a second processing stage, performing a second processing of the subset of the set of media recordings, the second processing including extraction of information from the media recordings of the subset of the set of media recordings. The first processing of each media recording of the set of media recordings includes determining a characterization of the media recording, the characterization including at least a quantity characterizing a predicted performance of the second processing of the media recording.

Abstract: A method for analysis of a set of media recordings includes, in a first processing stage, selecting a subset of the set of media recordings by performing a first processing of each media recording of the set of media recordings and in a second processing stage, performing a second processing of the subset of the set of media recordings, the second processing including extraction of information from the media recordings of the subset of the set of media recordings. The first processing of each media recording of the set of media recordings includes determining a characterization of the media recording, the characterization including at least a quantity characterizing a predicted performance of the second processing of the media recording.

Abstract: In one aspect, a method for processing media includes accepting a query. One or more language patterns are identified that are similar to the query. A putative instance of the query is located in the media. The putative instance is associated with a corresponding location in the media. The media in a vicinity of the putative instance is compared to the identified language patterns and data characterizing the putative instance of the query is provided according to the comparing of the media to the language patterns, for example, as a score for the putative instance that is determined according to the comparing of the media to the language patterns.

Abstract: Systems, methods, and apparatus, including computer program products for accepting a predetermined vocabulary-dependent characterization of a set of audio signals, the predetermined characterization including an identification of putative occurrences of each of a plurality of vocabulary items in the set of audio signals, the plurality of vocabulary items included in the vocabulary; accepting a new vocabulary item not included in the vocabulary; accepting putative occurrences of the new vocabulary item in the set of audio signals; and generating, by an analysis engine of a speech processing system, an augmented characterization of the set of audio signals based on the identified putative occurrences of the new vocabulary item.

Abstract: A method for speaker adaptation includes receiving a plurality of media files, each associated with a call center agent of a plurality of call center agents and receiving a plurality of terms. Speech processing is performed on at least some of the media files to identify putative instances of at least some of the plurality of terms. Each putative instance is associated with a hit quality that characterizes a quality of recognition of the corresponding term. One or more call center agents for performing speaker adaptation are determined, including identifying call center agents that are associated with at least one media file that includes one or more putative instances with a hit quality below a predetermined threshold. Speaker adaptation is performed for each identified call center agent based on the media files associated with the identified call center agent and the identified instances of the plurality of terms.

Abstract: An audio processing system makes use of a number of levels of compression or data reduction, thereby providing reduced storage requirements while maintaining a high accuracy of keyword detection in the original audio input.

Abstract: A method for determining a similarity between a first audio source and a second audio source includes: for the first audio source, determining a first frequency of occurrence for each of a plurality of phoneme sequences and determining a first weighted frequency for each of the plurality of phoneme sequences based on the first frequency of occurrence for the phoneme sequence; for the second audio source, determining a second frequency of occurrence for each of a plurality of phoneme sequences and determining a second weighted frequency for each of the plurality of phoneme sequences based on the second frequency of occurrence for the phoneme sequence; comparing the first weighted frequency for each phoneme sequence with the second weighted frequency for the corresponding phoneme sequence; and generating a similarity score representative of a similarity between the first audio source and the second audio source based on the results of the comparing.

Abstract: A method for speaker adaptation includes receiving a plurality of media files, each associated with a call center agent of a plurality of call center agents and receiving a plurality of terms. Speech processing is performed on at least some of the media files to identify putative instances of at least some of the plurality of terms. Each putative instance is associated with a hit quality that characterizes a quality of recognition of the corresponding term. One or more call center agents for performing speaker adaptation are determined, including identifying call center agents that are associated with at least one media file that includes one or more putative instances with a hit quality below a predetermined threshold. Speaker adaptation is performed for each identified call center agent based on the media files associated with the identified call center agent and the identified instances of the plurality of terms.

Abstract: In some aspects, a wordspotter is used to locate occurrences in an audio corpus of each of a set of predetermined subword units, which may be phoneme sequences. To locate a query (e.g., a keyword or phrase) in the audio corpus, constituent subword units in the query are indentified and then locations of those subwords are determined based on the locations of those subword units determined earlier by the wordspotter, for example, using a pre-built inverted index that maps subword units to their locations.

Abstract: An audio processing system makes use of a number of levels of compression or data reduction, thereby providing reduced storage requirements while maintaining a high accuracy of keyword detection in the original audio input.

Abstract: A method for determining a similarity between a first audio source and a second audio source includes: for the first audio source, determining a first frequency of occurrence for each of a plurality of phoneme sequences and determining a first weighted frequency for each of the plurality of phoneme sequences based on the first frequency of occurrence for the phoneme sequence; for the second audio source, determining a second frequency of occurrence for each of a plurality of phoneme sequences and determining a second weighted frequency for each of the plurality of phoneme sequences based on the second frequency of occurrence for the phoneme sequence; comparing the first weighted frequency for each phoneme sequence with the second weighted frequency for the corresponding phoneme sequence; and generating a similarity score representative of a similarity between the first audio source and the second audio source based on the results of the comparing.