公开(公告)号：US20240363123A1

公开(公告)日：2024-10-31

申请号：US18646310

申请日：2024-04-25

Applicant: Pindrop Security, Inc.

Inventor： Elie KHOURY ,  Ganesh SIVARAMAN ,  Tianxiang CHEN ,  Nikolay GAUBITCH ,  David LOONEY ,  Amit GUPTA ,  Vijay BALASUBRAMANIYAN ,  Nicholas KLEIN ,  Anthony STANKUS

IPC: G10L17/26 ,  G10L15/02

CPC classification number: G10L17/26 ,  G10L15/02

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. Embodiments include systems and methods for detecting fraudulent presentation attacks using multiple functional engines that implement various fraud-detection techniques, to produce calibrated scores and/or fused scores. A computer may, for example, evaluate the audio quality of speech signals within audio signals, where speech signals contain the speech portions having speaker utterances.

公开(公告)号：US20240363125A1

公开(公告)日：2024-10-31

申请号：US18646493

申请日：2024-04-25

Applicant: Pindrop Security, Inc.

Inventor： Elie KHOURY ,  Ganesh SIVARAMAN ,  Tianxiang CHEN ,  Nikolay GAUBITCH ,  David LOONEY ,  Amit GUPTA ,  Vijay BALASUBRAMANIYAN ,  Nicholas KLEIN ,  Anthony STANKUS

IPC: G10L17/26 ,  G10L17/02 ,  G10L17/04 ,  G10L25/60 ,  H04M3/22 ,  H04M3/51

CPC classification number: G10L17/26 ,  G10L17/02 ,  G10L17/04 ,  G10L25/60 ,  H04M3/2281 ,  H04M3/5183 ,  H04M2201/405

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. Embodiments include systems and methods for detecting fraudulent presentation attacks using multiple functional engines that implement various fraud-detection techniques, to produce calibrated scores and/or fused scores. A computer may, for example, evaluate the audio quality of speech signals within audio signals, where speech signals contain the speech portions having speaker utterances.

公开(公告)号：US20240363124A1

公开(公告)日：2024-10-31

申请号：US18646431

申请日：2024-04-25

Applicant: Pindrop Security, Inc.

Inventor： Elie KHOURY ,  Ganesh SIVARAMAN ,  Tianxiang CHEN ,  Nikolay GAUBITCH ,  David LOONEY ,  Amit GUPTA ,  Vijay BALASUBRAMANIYAN ,  Nicholas KLEIN ,  Anthony STANKUS

IPC: G10L17/26 ,  G10L17/02 ,  G10L17/04 ,  G10L17/08

CPC classification number: G10L17/26 ,  G10L17/02 ,  G10L17/04 ,  G10L17/08

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. Embodiments include systems and methods for detecting fraudulent presentation attacks using multiple functional engines that implement various fraud-detection techniques, to produce calibrated scores and/or fused scores. A computer may, for example, evaluate the audio quality of speech signals within audio signals, where speech signals contain the speech portions having speaker utterances.

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.

公开(公告)号：US20240363119A1

公开(公告)日：2024-10-31

申请号：US18646375

申请日：2024-04-25

Applicant: Pindrop Security, Inc.

Inventor： Elie KHOURY ,  Ganesh SIVARAMAN ,  Tianxiang CHEN ,  Nikolay GAUBITCH ,  David LOONEY ,  Amit GUPTA ,  Vijay BALASUBRAMANIYAN ,  Nicholas KLEIN ,  Anthony STANKUS

IPC: G10L17/00

CPC classification number: G10L17/00

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. Embodiments include systems and methods for detecting fraudulent presentation attacks using multiple functional engines that implement various fraud-detection techniques, to produce calibrated scores and/or fused scores. A computer may, for example, evaluate the audio quality of speech signals within audio signals, where speech signals contain the speech portions having speaker utterances.

公开(公告)号：US20240363100A1

公开(公告)日：2024-10-31

申请号：US18646228

申请日：2024-04-25

Applicant: Pindrop Security, Inc.

Inventor： Elie KHOURY ,  Ganesh SIVARAMAN ,  Tianxiang CHEN ,  Nikolay GAUBITCH ,  David LOONEY ,  Amit GUPTA ,  Vijay BALASUBRAMANIYAN ,  Nicholas KLEIN ,  Anthony STANKUS

IPC: G10L15/02

CPC classification number: G10L15/02

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. Embodiments include systems and methods for detecting fraudulent presentation attacks using multiple functional engines that implement various fraud-detection techniques, to produce calibrated scores and/or fused scores. A computer may, for example, evaluate the audio quality of speech signals within audio signals, where speech signals contain the speech portions having speaker utterances.

公开(公告)号：US20200312313A1

公开(公告)日：2020-10-01

申请号：US16829705

申请日：2020-03-25

Applicant: PINDROP SECURITY, INC.

Inventor： Vinay MADDALI ,  David LOONEY ,  Kailash PATIL

IPC: G10L15/197 ,  H04M3/51 ,  G10L15/18 ,  G10L15/02 ,  G10L15/04 ,  G10L25/21 ,  G10L15/06 ,  G10L15/22 ,  G10L25/84 ,  G06N20/00 ,  G06N5/04

Abstract: Embodiments described herein provide for automatically classifying the types of devices that place calls to a call center. A call center system can detect whether an incoming call originated from voice assistant device using trained classification models received from a call analysis service. Embodiments described herein provide for methods and systems in which a computer executes machine learning algorithms that programmatically train (or otherwise generate) global or tailored classification models based on the various types of features of an audio signal and call data. A classification model is deployed to one or more call centers, where the model is used by call center computers executing classification processes for determining whether incoming telephone calls originated from a voice assistant device, such as Amazon Alexa® and Google Home®, or another type of device (e.g., cellular/mobile phone, landline phone, VoIP).

公开(公告)号：US20190311730A1

公开(公告)日：2019-10-10

申请号：US16375785

申请日：2019-04-04

Applicant: PINDROP SECURITY, INC.

Inventor： David LOONEY ,  Nikolay D. GAUBITCH

IPC: G10L25/51 ,  G10L25/90 ,  G10L15/22 ,  G10L15/06

Abstract: A computer may train a single-class machine learning using normal speech recordings. The machine learning model or any other model may estimate the normal range of parameters of a physical speech production model based on the normal speech recordings. For example, the computer may use a source-filter model of speech production, where voiced speech is represented by a pulse train and unvoiced speech by a random noise and a combination of the pulse train and the random noise is passed through an auto-regressive filter that emulates the human vocal tract. The computer leverages the fact that intentional modification of human voice introduces errors to source-filter model or any other physical model of speech production. The computer may identify anomalies in the physical model to generate a voice modification score for an audio signal. The voice modification score may indicate a degree of abnormality of human voice in the audio signal.