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公开(公告)号:US20240355337A1
公开(公告)日:2024-10-24
申请号:US18388364
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: G10L17/24
CPC分类号: G10L17/24
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:US20230284016A1
公开(公告)日:2023-09-07
申请号:US18117134
申请日:2023-03-03
发明人: MohammedAli Merchant , Yitao Sun
IPC分类号: H04W12/069 , H04W12/40 , H04W12/72
CPC分类号: H04W12/069 , H04W12/40 , H04W12/72
摘要: Embodiments described herein provide for evaluating call metadata and certificates of inbound calls for authentication. The computer identifies a service provider indicated by the SPID and/or the ANI (or other identifier) of the metadata and identifies a service provider indicated by the SPID and/or ANI (or other identifier) of the certificate, then compares identities of the service providers and/or compares the data values associated with the service providers (e.g., SPIDs, ANIs). Based on this comparison, the computer determines whether the service provider that signed the certificate is first-party signer (e.g., carrier) for the ANI or a third-party signer that is signing certificates as the first-party signer for the ANI.
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公开(公告)号:US20230262161A1
公开(公告)日:2023-08-17
申请号:US18109095
申请日:2023-02-13
发明人: Mohammed Ali Merchant , Yitao Sun
CPC分类号: H04M3/42059 , H04M3/2281 , H04M3/42357 , H04M2203/6027
摘要: Embodiments described herein provide for systems and methods for verifying authentic JIPs associated with ANIs using CLLIs known to be associated with the ANIs, allowing a computer to authenticate calls using the verified JIPs, among various factors. The computer builds a trust model for JIPs by correlating unique CLLIs to JIPs. A malicious actor might spoof numerous ANIs mapped to a single CLLI, but the malicious actor is unlikely to spoof multiple CLLIs due to the complexity of spoofing the volumes of ANIs associated with multiple CLLIs, so the CLLIs can be trusted when determining whether a JIP is authentic. The computer identifies an authentic JIP when the trust model indicates that a number of CLLIs associated with the JIP satisfies one or more thresholds. A machine-learning architecture references the fact that the JIP is authentic as an authentication factor for downstream call authentication functions.
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公开(公告)号:US20240363099A1
公开(公告)日:2024-10-31
申请号:US18388466
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
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:US20240355319A1
公开(公告)日:2024-10-24
申请号:US18388385
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
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:US20240363103A1
公开(公告)日:2024-10-31
申请号:US18388412
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: G10L15/08
CPC分类号: G10L15/08
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:US20240355322A1
公开(公告)日:2024-10-24
申请号:US18388428
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: G10L15/08
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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