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公开(公告)号：US20240363123A1
公开(公告)日：2024-10-31
申请号：US18646310
申请日：2024-04-25
发明人： Elie KHOURY , Ganesh SIVARAMAN , Tianxiang CHEN , Nikolay GAUBITCH , David LOONEY , Amit GUPTA , Vijay BALASUBRAMANIYAN , Nicholas KLEIN , Anthony STANKUS
摘要： 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.
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公开(公告)号：US20180152561A1
公开(公告)日：2018-05-31
申请号：US15880287
申请日：2018-01-25
发明人： Scott STRONG , Kailash PATIL , David DEWEY , Raj BANDYOPADHYAY , Telvis CALHOUN , Vijay BALASUBRAMANIYAN
CPC分类号： H04M3/527 , G06F21/32 , G06F21/552 , G06N20/00 , H04M3/493 , H04M7/0078 , H04M15/41 , H04M2203/551 , H04M2203/6027 , H04W12/12
摘要： Systems and methods for call detail record (CDR) analysis to determine a risk score for a call and identify fraudulent activity and for fraud detection in Interactive Voice Response (IVR) systems. An example method may store information extracted from received calls. Queries of the stored information may be performed to select data using keys, wherein each key relates to one of the received calls, and wherein the queries are parallelized. The selected data may be transformed into feature vectors, wherein each feature vector relates to one of the received calls and includes a velocity feature and at least one of a behavior feature or a reputation feature. A risk score for the call may be generated during the call based on the feature vectors.
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公开(公告)号：US20170111515A1
公开(公告)日：2017-04-20
申请号：US15294576
申请日：2016-10-14
发明人： Raj BANDYOPADHYAY , Kailash PATIL , David DEWEY , Scott STRONG , Telvis CALHOUN , Vijay BALASUBRAMANIYAN
CPC分类号： H04M3/527 , G06F21/32 , G06F21/552 , G06N99/005 , H04M3/493 , H04M7/0078 , H04M15/41 , H04M2203/551 , H04M2203/6027 , H04W12/12
摘要： Systems and methods for call detail record (CDR) analysis to determine a risk score for a call and identify fraudulent activity and for fraud detection in Interactive Voice Response (IVR) systems. An example method may store information extracted from received calls. Queries of the stored information may be performed to select data using keys, wherein each key relates to one of the received calls, and wherein the queries are parallelized. The selected data may be transformed into feature vectors, wherein each feature vector relates to one of the received calls and includes a velocity feature and at least one of a behavior feature or a reputation feature. A risk score for the call may be generated during the call based on the feature vectors.
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公开(公告)号：US20240363125A1
公开(公告)日：2024-10-31
申请号：US18646493
申请日：2024-04-25
发明人： Elie KHOURY , Ganesh SIVARAMAN , Tianxiang CHEN , Nikolay GAUBITCH , David LOONEY , Amit GUPTA , Vijay BALASUBRAMANIYAN , Nicholas KLEIN , Anthony STANKUS
CPC分类号： G10L17/26 , G10L17/02 , G10L17/04 , G10L25/60 , H04M3/2281 , H04M3/5183 , H04M2201/405
摘要： 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.
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公开(公告)号：US20240355334A1
公开(公告)日：2024-10-24
申请号：US18388457
申请日：2023-11-09
发明人： Umair Altaf , Sai Pradeep PERI , Lakshay PHATELA , Payas GUPTA , Yitao SUN , Svetlana AFANASEVA , Kailash PATIL , Elie KHOURY , Bradley MAGNETTA , Vijay BALASUBRAMANIYAN , Tianxiang CHEN
IPC分类号： G10L17/06
CPC分类号： G10L17/06
摘要： Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.
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公开(公告)号：US20190342452A1
公开(公告)日：2019-11-07
申请号：US16515823
申请日：2019-07-18
发明人： Scott STRONG , Kailash PATIL , David DEWEY , Raj BANDYOPADHYAY , Telvis CALHOUN , Vijay BALASUBRAMANIYAN
摘要： Systems and methods for call detail record (CDR) analysis to determine a risk score for a call and identify fraudulent activity and for fraud detection in Interactive Voice Response (IVR) systems. An example method may store information extracted from received calls. Queries of the stored information may be performed to select data using keys, wherein each key relates to one of the received calls, and wherein the queries are parallelized. The selected data may be transformed into feature vectors, wherein each feature vector relates to one of the received calls and includes a velocity feature and at least one of a behavior feature or a reputation feature. A risk score for the call may be generated during the call based on the feature vectors.
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公开(公告)号：US20240355323A1
公开(公告)日：2024-10-24
申请号：US18388447
申请日：2023-11-09
发明人： Umair Altaf , Sai Pradeep PERI , Lakshay PHATELA , Payas GUPTA , Yitao SUN , Svetlane AFANASEVA , Kailash PATIL , Elie KHOURY , Bradley MAGNETTA , Vijay BALASUBRAMANIYAN , Tianxiang CHEN
摘要： Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.
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公开(公告)号：US20220392453A1
公开(公告)日：2022-12-08
申请号：US17832404
申请日：2022-06-03
摘要： Disclosed are systems and methods including computing-processes executing machine-learning architectures extract vectors representing disparate types of data and output predicted identities of users accessing computing services, without express identity assertions, and across multiple computing services, analyzing data from multiple modalities, for various user devices, and agnostic to architectures hosting the disparate computing service. The system invokes the identification operations of the machine-learning architecture, which extracts biometric embeddings from biometric data and context embeddings representing all or most of the types of metadata features analyzed by the system. The context embeddings help identify a subset of potentially matching identities of possible users, which limits the number of biometric-prints the system compares against an inbound biometric embedding for authentication. The types of extracted features originate from multiple modalities, including metadata from data communications, audio signals, and images. In this way, the embodiments apply a multi-modality machine-learning architecture.
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公开(公告)号：US20240363124A1
公开(公告)日：2024-10-31
申请号：US18646431
申请日：2024-04-25
发明人： Elie KHOURY , Ganesh SIVARAMAN , Tianxiang CHEN , Nikolay GAUBITCH , David LOONEY , Amit GUPTA , Vijay BALASUBRAMANIYAN , Nicholas KLEIN , Anthony STANKUS
摘要： 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.
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公开(公告)号：US20240355336A1
公开(公告)日：2024-10-24
申请号：US18439049
申请日：2024-02-12
发明人： Umair ALTAF , Sai Pradeep PERI , Lakshay PHATELA , Payas GUPTA , Yitao SUN , Svetlana AFANASEVA , Kailash PATIL , Elie KHOURY , Bradley MAGNETTA , Vijay BALASUBRAMANIYAN , Tianxiang CHEN
摘要： Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.
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