SYSTEM AND METHOD FOR DETECTING STRESS IN AUDIO DATA

    公开(公告)号:US20250006218A1

    公开(公告)日:2025-01-02

    申请号:US18216699

    申请日:2023-06-30

    Applicant: NICE LTD.

    Inventor: Tal HAGUEL

    Abstract: A computerized system and method may process and predict stress levels for audio data using a machine learning based framework. A computerized system including a processor and a memory may calculate a buffer length based on a plurality of audio attributes (e.g., of a given audio input or data item), extract an audio buffer from an audio data item based on the calculated length, and predict, using a machine learning model, a stress level for the audio buffer or data item. Some embodiments of the invention may include extracting a buffer of a length determined dynamically for different audio inputs, e.g., to ensure coherency between audio attributes or features extracted from different audio inputs having different audio characteristics. In some embodiments, audio features which may be considered by the model may include, e.g., a plurality of gradients between mel-frequency cepstrum coefficients computed for relevant audio buffers or inputs.

    BIOMETRIC AUTHENTICATION THROUGH VOICE PRINT CATEGORIZATION USING ARTIFICIAL INTELLIGENCE

    公开(公告)号:US20220358933A1

    公开(公告)日:2022-11-10

    申请号:US17313040

    申请日:2021-05-06

    Applicant: NICE LTD.

    Abstract: A system is provided to categorize voice prints during a voice authentication. The system includes a processor and a computer readable medium operably coupled thereto, to perform voice authentication operations which include receiving an enrollment of a user in the biometric authentication system, requesting a first voice print comprising a sample of a voice of the user, receiving the first voice print of the user during the enrollment, accessing a plurality of categorizations of the voice prints for the voice authentication, wherein each of the plurality of categorizations comprises a portion of the voice prints based on a plurality of similarity scores of distinct voice prints in the portion to a plurality of other voice prints, determining, using a hidden layer of a neural network, one of the plurality of categorizations for the first voice print, and encoding the first voice print with the one of the plurality of categorizations.

    ARTIFICIAL INTELLIGENCE MODEL FOR PREDICTING PLAYBACK OF MEDIA DATA

    公开(公告)号:US20220012281A1

    公开(公告)日:2022-01-13

    申请号:US16927388

    申请日:2020-07-13

    Applicant: NICE LTD.

    Abstract: A system is provided to predict requested playbacks of media files by users from a media storage system. The system includes a processor and a computer readable medium operably coupled thereto, to perform predictive playback operations which include accessing an AI model and a media file comprising metadata associated with generating the media file, generating a predictive score for a playback of the media file based on the AI model and the metadata, comparing the predictive score to a threshold required to transcode the media file into a playback format prior to the playback, predicting the playback based on the comparing, determining a predicted playback time of the media file based on the metadata for the media file, and transcoding the media file into the playback format prior to the predicted playback time.

    SYSTEM AND METHOD FOR SCORE NORMALIZATION

    公开(公告)号:US20240371368A1

    公开(公告)日:2024-11-07

    申请号:US18312146

    申请日:2023-05-04

    Applicant: Nice Ltd.

    Abstract: Systems and methods for mapping a set of output values of a first learning model to a distribution of a set of output values of a second learning model include: calculating a distribution function for a set of source values; calculating a distribution function for a set of target values; calculating a set of quantiles for each distribution function; using the set of quantiles in a linear interpolation of the set of target values to obtain a source values array and a matched interpolated values array; calculating an absolute distance from each value in the source values array to the first set of output values of the first learning model; determining a corresponding value in the matched interpolated values array corresponding to a value in the source values array which has the smallest said absolute distance; and outputting a set of matched values.

    SEMANTIC SEARCH SYSTEMS AND METHODS
    6.
    发明公开

    公开(公告)号:US20230281236A1

    公开(公告)日:2023-09-07

    申请号:US17684034

    申请日:2022-03-01

    Applicant: NICE LTD

    CPC classification number: G06F16/355 G06F16/93 G06F40/30 G06F40/279

    Abstract: Semantic search systems and methods, and non-transitory computer readable media, include receiving divided text of at least two participants from a customer interaction; applying a clustering algorithm to the divided text to create a plurality of word clusters per participant, wherein each word cluster comprises topic words, phrases, or sentences; applying a word-embedding algorithm to the topic words, phrases, or sentences in each word cluster to produce a numeric representation of each word cluster; and storing the numeric representation of each word cluster and the topic words, phrases, or sentences in each word cluster in a document.

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