公开(公告)号：US11488605B2

公开(公告)日：2022-11-01

申请号：US16907951

申请日：2020-06-22

Applicant: PINDROP SECURITY, INC.

Inventor： Elie Khoury ,  Parav Nagarsheth ,  Kailash Patil ,  Matthew Garland

IPC: G10L17/02 ,  G10L17/04 ,  G10L25/24 ,  G10L17/18 ,  G10L19/02 ,  G10L17/06 ,  G10L17/00 ,  G10L25/51 ,  G10L25/30

Abstract: An automated speaker verification (ASV) system incorporates a first deep neural network to extract deep acoustic features, such as deep CQCC features, from a received voice sample. The deep acoustic features are processed by a second deep neural network that classifies the deep acoustic features according to a determined likelihood of including a spoofing condition. A binary classifier then classifies the voice sample as being genuine or spoofed.

公开(公告)号：US12015637B2

公开(公告)日：2024-06-18

申请号：US16841473

申请日：2020-04-06

Applicant: PINDROP SECURITY, INC.

Inventor： Khaled Lakhdhar ,  Parav Nagarsheth ,  Tianxiang Chen ,  Elie Khoury

IPC: H04L9/40 ,  G06F17/18 ,  G06N3/045 ,  G06N3/084 ,  G06N20/10 ,  G10L17/00 ,  G10L17/04 ,  G10L17/26 ,  G10L19/26 ,  H04L65/75

CPC classification number: H04L63/1466 ,  G06F17/18 ,  G06N3/045 ,  G06N3/084 ,  G06N20/10 ,  G10L17/00 ,  G10L17/04 ,  G10L17/26 ,  G10L19/26 ,  H04L65/75

Abstract: Embodiments described herein provide for automatically detecting whether an audio signal is a spoofed audio signal or a genuine audio signal. A spoof detection system can include an audio signal transforming front end and a classification back end. Both the front end and the back end can include neural networks that can be trained using the same set of labeled audio signals. The audio signal transforming front end can include a one or more neural networks for per-channel energy normalization transformation of the audio signal, and the back end can include a convolution neural network for classification into spoofed or genuine audio signal. In some embodiments, the transforming audio signal front end can include one or more neural networks for bandpass filtering of the audio signals, and the back end can include a residual neural network for audio signal classification into spoofed or genuine audio signal.

公开(公告)号：US10692502B2

公开(公告)日：2020-06-23

申请号：US15910387

申请日：2018-03-02

Applicant: PINDROP SECURITY, INC.

Inventor： Elie Khoury ,  Parav Nagarsheth ,  Kailash Patil ,  Matthew Garland

IPC: G10L17/02 ,  G10L17/04 ,  G10L17/06 ,  G10L17/18 ,  G10L19/02 ,  G10L25/24 ,  G10L17/00

Abstract: An automated speaker verification (ASV) system incorporates a first deep neural network to extract deep acoustic features, such as deep CQCC features, from a received voice sample. The deep acoustic features are processed by a second deep neural network that classifies the deep acoustic features according to a determined likelihood of including a spoofing condition. A binary classifier then classifies the voice sample as being genuine or spoofed.