IMPROVED FIXED POINT INTEGER IMPLEMENTATIONS FOR NEURAL NETWORKS

    公开(公告)号:US20170220929A1

    公开(公告)日:2017-08-03

    申请号:US15500405

    申请日:2014-09-09

    Abstract: Techniques related to implementing neural networks for speech recognition systems are discussed. Such techniques may include processing a node of the neural network by determining a score for the node as a product of weights and inputs such that the weights are fixed point integer values, applying a correction to the score based a correction value associated with at least one of the weights, and generating an output from the node based on the corrected score.

    DEEPFAKE DETECTION MODELS UTILIZING SUBJECT-SPECIFIC LIBRARIES

    公开(公告)号:US20220004904A1

    公开(公告)日:2022-01-06

    申请号:US17481475

    申请日:2021-09-22

    Abstract: An apparatus to facilitate deepfake detection models utilizing subject-specific libraries is disclosed. The apparatus includes one or more processors to store a plurality of deepfake detection models corresponding to a plurality of subjects of interest; receive a query to identify whether data pertaining to a target subject of interest is a deepfake, the target subject of interest comprised in the plurality of subjects of interest and associated with a subject identifier (ID); identify a deepfake detection model corresponding to the subject ID; extract features for deepfake detection from the data; input the extracted features to the identified deepfake detection model corresponding to the subject ID; and responsive to an output of the deepfake detection model exceeding a determined deepfake threshold, generate a notification, in response to the query, indicating a possible deepfake attack corresponding to the target subject of interest.

    Optimizations to decoding of WFST models for automatic speech recognition

    公开(公告)号:US10127902B2

    公开(公告)日:2018-11-13

    申请号:US15615799

    申请日:2017-06-06

    Abstract: A method in a computing device for decoding a weighted finite state transducer (WFST) for automatic speech recognition is described. The method includes sorting a set of one or more WFST arcs based on their arc weight in ascending order. The method further includes iterating through each arc in the sorted set of arcs according to the ascending order until the score of the generated token corresponding to an arc exceeds a score threshold. The method further includes discarding any remaining arcs in the set of arcs that have yet to be considered.

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