公开(公告)号：US11924367B1

公开(公告)日：2024-03-05

申请号：US17668297

申请日：2022-02-09

Applicant: Amazon Technologies, Inc.

Inventor： Jean-Marc Valin ,  Karim Helwani ,  Srikanth Venkata Tenneti ,  Erfan Soltanmohammadi ,  Mehmet Umut Isik ,  Richard Newman ,  Michael Mark Goodwin ,  Arvindh Krishnaswamy

IPC: H04M3/00 ,  G10L21/0232 ,  G10L21/034 ,  G10L25/18 ,  H04S3/00 ,  G10L21/0208

CPC classification number: H04M3/002 ,  G10L21/0232 ,  G10L21/034 ,  G10L25/18 ,  H04S3/008 ,  G10L2021/02082 ,  H04S2400/01 ,  H04S2400/03

Abstract: Joint noise and echo suppression may be performed for enhancing two-way audio communications. Audio data is captured at a communication device and audio data transmitted to the communication device from another communication device are used as input features to a trained machine learning model that uses the transmitted audio data as a reference signal to eliminate residual echo in the captured audio data when also suppressing noise in the captured audio data.

公开(公告)号：US12205039B1

公开(公告)日：2025-01-21

申请号：US17087181

申请日：2020-11-02

Applicant: Amazon Technologies, Inc.

Inventor： Ritwik Giri ,  Srikanth Venkata Tenneti ,  Karim Helwani ,  Fangzhou Cheng ,  Mehmet Umut Isik ,  Arvindh Krishnaswamy

IPC: G06N3/088 ,  G10L25/03 ,  G10L25/51

Abstract: A group masked autoencoder may be implemented for anomaly detection. An autoencoder network model may be trained without supervision and applied to output an estimated joint probability distribution of normality for a group of frames of time series data. The estimated joint probability distribution may be used to determine an anomaly score for the time series data. An anomaly may be detected according to the anomaly score and a result that indicates a detected anomaly may be provided.

公开(公告)号：US12175434B2

公开(公告)日：2024-12-24

申请号：US17039649

申请日：2020-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Srikanth Venkata Tenneti ,  Arvindh Krishnaswamy ,  Karim Helwani ,  Mehmet Umut Isik ,  Ritwik Giri ,  Fangzhou Cheng ,  Aparna Pandey

IPC: G06Q10/20 ,  G06F16/21 ,  G06F16/906

Abstract: Systems, methods, and apparatuses for detecting anomalies using clusters are described. In some examples, a method includes receiving a request to perform anomaly detection using a plurality of clusters; receiving a data point; determining when the received data point is a part of one of the plurality of clusters utilizing a distance to centers of the one or more clusters, wherein: when the received data point is determined to belong to a normal cluster, assigning the received data point to the determined cluster, updating the cluster, and updating a history for the cluster, when the received data point is determined to belong to an anomalous cluster, raising an anomaly, updating the cluster, and updating a history for the cluster, and when the received data point is determined to not belong to any cluster, raising an anomaly.

公开(公告)号：US20220101270A1

公开(公告)日：2022-03-31

申请号：US17039649

申请日：2020-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Srikanth Venkata Tenneti ,  Arvindh Krishnaswamy ,  Karim Helwani ,  Mehmet Umut Isik ,  Ritwik Giri ,  Fangzhou Cheng ,  Aparna Pandey

IPC: G06Q10/00 ,  G06F16/906 ,  G06F16/21

Abstract: Systems, methods, and apparatuses for detecting anomalies using clusters are described. In some examples, a method includes receiving a request to perform anomaly detection using a plurality of clusters; receiving a data point; determining when the received data point is a part of one of the plurality of clusters utilizing a distance to centers of the one or more clusters, wherein: when the received data point is determined to belong to a normal cluster, assigning the received data point to the determined cluster, updating the cluster, and updating a history for the cluster, when the received data point is determined to belong to an anomalous cluster, raising an anomaly, updating the cluster, and updating a history for the cluster, and when the received data point is determined to not belong to any cluster, raising an anomaly.