中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

185 records (took 0.024 seconds)

    Call authentication at the call center using a mobile device
    101.
    发明授权
    Call authentication at the call center using a mobile device 有权

    公开(公告)号：US12212709B2

    公开(公告)日：2025-01-28

    申请号：US17004921

    申请日：2020-08-27

    Applicant: PINDROP SECURITY, INC.

    Inventor： Payas Gupta ,  Terry Nelms, II

    IPC: H04M3/42 ,  H04W12/06

    Abstract: Embodiments described herein provide for automatically authenticating telephone calls to an enterprise call center. The system disclosed herein builds on the trust of a data channel for the telephony channel. Certain types of authentication information can be received through the telephony channel, as well. But the mobile application associated with the call center system may provide additional or alternative forms of data through the data channel. The system may send requests to a mobile application of a device to provide information that can reliably be assumed to be coming from that particular device, such as a state of the device and/or a user's response to push notifications. In some cases, the authentication processes may be based on quantity and quality of matches between certain metadata or attributes expected to be received from a given device as compared to the metadata or attributes received.

    CENTRALIZED SYNTHETIC SPEECH DETECTION SYSTEM USING WATERMARKING
    102.
    发明申请
    CENTRALIZED SYNTHETIC SPEECH DETECTION SYSTEM USING WATERMARKING 有权

    公开(公告)号：US20250029614A1

    公开(公告)日：2025-01-23

    申请号：US18777278

    申请日：2024-07-18

    Applicant: PINDROP SECURITY, INC.

    Inventor： David LOONEY ,  Nikolay GAUBITCH ,  Elie KHOURY

    IPC: G10L17/02

    Abstract: Disclosed are systems and methods including software processes executed by a server for obtaining, by a computer, an audio signal including synthetic speech, extracting, by the computer, metadata from a watermark of the audio signal by applying a set of keys associated with a plurality of text-to-speech (TTS) services to the audio signal, the metadata indicating an origin of the synthetic speech in the audio signal, and generating, by the computer, based on the extracted metadata, a notification indicating that the audio signal includes the synthetic speech.

    PRESENTATION ATTACKS IN REVERBERANT CONDITIONS
    106.
    发明公开
    PRESENTATION ATTACKS IN REVERBERANT CONDITIONS 审中-公开

    公开(公告)号：US20240311474A1

    公开(公告)日：2024-09-19

    申请号：US18598595

    申请日：2024-03-07

    Applicant: PINDROP SECURITY, INC.

    Inventor： Nikolay Gaubitch ,  David Looney

    IPC: G06F21/55 ,  G06N20/00 ,  G10L25/18 ,  G10L25/51 ,  G10L25/69

    CPC classification number: G06F21/554 ,  G06N20/00 ,  G10L25/18 ,  G10L25/51 ,  G10L25/69 ,  G06F2221/034

    Abstract: Embodiments include a computing device that executes software routines and/or one or more machine-learning architectures including obtaining training audio signals having corresponding training impulse responses associated with reverberation degradation, training a machine-learning model of a presentation attack detection engine to generate one or more acoustic parameters by executing the presentation attack detection engine using the training impulse responses of the training audio signals and a loss function, obtaining an audio signal having an acoustic impulse response associated with reverberation degradation caused by one or more rooms, generating the one or more acoustic parameters for the audio signal by executing the machine-learning model using the audio signal as input, and generating an attack score for the audio signal based upon the one or more parameters generated by the machine-learning model.

    Joint estimation of acoustic parameters from single-microphone speech
    107.
    发明授权
    Joint estimation of acoustic parameters from single-microphone speech 有权

    公开(公告)号：US12087319B1

    公开(公告)日：2024-09-10

    申请号：US17079082

    申请日：2020-10-23

    Applicant: PINDROP SECURITY, INC.

    Inventor： David Looney ,  Nikolay Gaubitch

    IPC: G10L25/30 ,  G06N3/048 ,  G06N3/08

    CPC classification number: G10L25/30 ,  G06N3/048 ,  G06N3/08

    Abstract: Embodiments described herein provide for end-to-end joint determination of degradation parameter scores for certain types of degradation. Degradation parameters include degradation describing additive noise and multiplicative noise such as Signal-to-Noise Ratio (SNR), reverberation time (T60), and Direct-to-Reverberant Ratio (DRR). Various neural network architectures are described such that the inherent interplay between the degradation parameters is considered in both the degradation parameter score and degradation score determination. The neural network architectures are trained according to computer generated audio datasets.

    FRAUD IMPORTANCE SYSTEM
    108.
    发明公开
    FRAUD IMPORTANCE SYSTEM 审中-公开

    公开(公告)号：US20240214490A1

    公开(公告)日：2024-06-27

    申请号：US18432316

    申请日：2024-02-05

    Applicant: PINDROP SECURITY, INC.

    Inventor： Kedar PHATAK ,  Jayaram RAGHURAM

    IPC: H04M3/22 ,  G06N20/00 ,  H04L9/40

    CPC classification number: H04M3/2281 ,  G06N20/00 ,  H04L63/1483

    Abstract: Embodiments described herein provide for a fraud detection engine for detecting various types of fraud at a call center and a fraud importance engine for tailoring the fraud detection operations to relative importance of fraud events. Fraud importance engine determines which fraud events are comparative more important than others. The fraud detection engine comprises machine-learning models that consume contact data and fraud importance information for various anti-fraud processes. The fraud importance engine calculates importance scores for fraud events based on user-customized attributes, such as fraud-type or fraud activity. The fraud importance scores are used in various processes, such as model training, model selection, and selecting weights or hyper-parameters for the ML models, among others. The fraud detection engine uses the importance scores to prioritize fraud alerts for review. The fraud importance engine receives detection feedback, which contacts involved false negatives, where fraud events were undetected but should have been detected.

Patent Agency Ranking