System and method for real-time fraud detection in voice biometric systems using phonemes in fraudster voice prints

    公开(公告)号:US12236438B2

    公开(公告)日:2025-02-25

    申请号:US17568408

    申请日:2022-01-04

    Applicant: NICE Ltd.

    Abstract: A system and method for real-time fraud detection with a social engineering phoneme (SEP) watchlist of phoneme sequences may perform real-time fraud prevention operations including receiving incoming call interactions and grouping the call interactions into one or more clusters, each cluster associated with a speaker's voice based on voiceprints. For a pair of voiceprints in a cluster, a phoneme sequence is extracted for each voice print. From the extracted phoneme sequences, a similarity score is then calculated to determine if a match exists between the extracted phoneme sequences based on a threshold. If determined a match exists, the phoneme sequence may be added to a SEP watchlist.

    System and method for detecting fraudsters

    公开(公告)号:US12020711B2

    公开(公告)日:2024-06-25

    申请号:US17166525

    申请日:2021-02-03

    Applicant: Nice Ltd.

    CPC classification number: G10L17/08 G06Q50/26 G10L15/22 G10L17/04

    Abstract: A system and method may classify a plurality of interactions, by: obtaining a plurality of voiceprints of the plurality of interactions, wherein each voiceprint of the plurality of voiceprints represents a speaker participating in an interaction of the plurality of interactions; calculating, for each interaction, a plurality of scores, wherein each score of the plurality of scores is indicative of a similarity between the voiceprint of the interaction and one voiceprint of a set of benchmark voiceprints; calculating, for each interaction, statistics of the scores; and determining that a plurality of interactions pertain to a single cluster of interactions based on statistics of the scores of the interactions in the cluster.

    Computerized monitoring of digital audio signals

    公开(公告)号:US11984129B2

    公开(公告)日:2024-05-14

    申请号:US18064638

    申请日:2022-12-12

    Applicant: NICE LTD.

    CPC classification number: G10L19/00 G10L17/02 G10L25/30

    Abstract: A digital audio quality monitoring device uses a deep neural network (DNN) to provide accurate estimates of signal-to-noise ratio (SNR) from a limited set of features extracted from incoming audio. Some embodiments improve the SNR estimate accuracy by selecting a DNN model from a plurality of available models based on a codec used to compress/decompress the incoming audio. Each model has been trained on audio compressed/decompressed by a codec associated with the model, and the monitoring device selects the model associated with the codec used to compress/decompress the incoming audio. Other embodiments are also provided.

    Fraud detection in voice biometric systems through voice print clustering

    公开(公告)号:US11960584B2

    公开(公告)日:2024-04-16

    申请号:US17464817

    申请日:2021-09-02

    Applicant: NICE LTD.

    CPC classification number: G06F21/32 G10L17/12 G10L25/51

    Abstract: A system is provided for fraud prevention upscaling with a fraudster voice print watchlist. The system includes a processor and a computer readable medium operably coupled thereto, to perform fraud prevention operations which include receiving a first voice print of a user during a voice authentication request, accessing the fraudster voice print watchlist comprising voice print representatives for a plurality of voice print clusters each having one or more of a plurality of voice prints identified as fraudulent for a voice biometric system, determining that one or more of the voice print representatives in the fraudster voice print watchlist meets or exceeds a first biometric threshold for risk detection of the first voice print during the fraud prevention operations, and determining whether the first voice print matches a first one of the plurality of voice print clusters.

    Method and system for fraud clustering by content and biometrics analysis

    公开(公告)号:US11108910B2

    公开(公告)日:2021-08-31

    申请号:US17129986

    申请日:2020-12-22

    Applicant: NICE LTD

    Abstract: A computer-implemented method for proactive fraudster exposure in a customer service center according to content analysis and voice biometrics analysis, is provided herein. The computer-implemented method includes: (i) collecting call interaction; (ii) storing the collected call interactions; (iii) performing a first type analysis to cluster the call interactions into ranked clusters and storing the ranked clusters in a clusters database; (iv) performing a second type analysis on a predefined amount of the highest ranked clusters, into ranked clusters and storing the ranked clusters; the first type analysis is a content analysis and the second type analysis is a voice biometrics analysis, or vice versa; (v) retrieving from the ranked clusters, a list of fraudsters; and (vi) transmitting the list of potential fraudsters to an application to display to a user said list of potential fraudsters via a display unit.

    System and method for updating biometric evaluation systems

    公开(公告)号:US11841932B2

    公开(公告)日:2023-12-12

    申请号:US16847919

    申请日:2020-04-14

    Applicant: Nice Ltd.

    CPC classification number: G06F21/32 G06F16/2379 G06F16/68

    Abstract: A system and method may adjust the threshold or other settings in a biometric comparison system, or provide a report or display of parameters. Over a series of comparisons of authentication biometric samples (e.g. authentication VPs) to enrollment biometric samples (e.g. enrollment VPs), the authentication samples may be stored, and scores resulting from the biometric comparisons may be stored in a first set of scores. A second set of biometric comparisons may be created, each using a pairing of a stored authentication biometric sample and an enrollment biometric sample, each biometric comparison resulting in a score, the scores forming a second set of scores. The first and second sets of scores may be combined to produce a third set of scores, and an iterative process may be performed over the third set of scores to update the parameters of the Gaussian distribution of the third set of scores.

    Graph-based approach for voice authentication

    公开(公告)号:US11705134B2

    公开(公告)日:2023-07-18

    申请号:US17314176

    申请日:2021-05-07

    Applicant: NICE LTD.

    CPC classification number: G10L17/00 G10L17/06

    Abstract: Methods for voice authentication include receiving a plurality of mono telephonic interactions between customers and agents; creating a mapping of the plurality of mono telephonic interactions that illustrates which agent interacted with which customer in each of the interactions; determining how many agents each customer interacted with; identifying one or more customers an agent has interacted with that have the fewest interactions with other agents; and selecting a predetermined number of interactions of the agent with each of the identified customers. In some embodiments, the methods further include creating a voice print from first and second speaker components of each interaction; comparing the voice prints of a first selected interaction to the voice prints from a second selected interaction; calculating a similarity score between the voice prints; aggregating scores; and identifying the voice prints that are associated with the agent.

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