公开(公告)号：US20220130389A1

公开(公告)日：2022-04-28

申请号：US17573014

申请日：2022-01-11

Applicant: Amazon Technologies, Inc.

Inventor： Mark Conrad Kockerbeck ,  Muhammad Yahia ,  Jordan Michael Hughes ,  Kevin Boehm ,  Rohit Sauhta

IPC: G10L15/22 ,  G10L15/30 ,  G10L15/18

Abstract: The present disclosure describes techniques for dynamically determining when information is to be output to a user, as well as what information is to be output to a user. A natural language processing system may receive, from a first device, first data representing information to be output at a first point during a skill session. The natural language processing system may also receive, from a second device, second data representing a natural language input. The natural language processing system may determine a skill component is to execute with respect to the natural language input. The natural language processing system may send, to the skill component, second data representing the natural language input. The natural language processing system may receive, from the skill component, an indication that an ongoing first skill session with the second device has reached the first point. After receiving the indication and based at least in part on system usage data associated with at least one user, the natural language processing system may determine third data representing a prompt corresponding to the information and send, to the second device, the third data for output.

公开(公告)号：US11423208B1

公开(公告)日：2022-08-23

申请号：US15826379

申请日：2017-11-29

Applicant: Amazon Technologies, Inc.

Inventor： Manolya McCormick ,  Muhammad Yahia

IPC: G06F40/126 ,  G06F16/338 ,  G06F16/33 ,  G06F40/103 ,  G06F40/166 ,  G06F40/232

Abstract: Method and apparatus for detecting text encoding errors caused by previously encoding the electronic document in multiple encoding formats. Non-word portions are removed from the electronic document. Embodiments determine whether words in the electronic document are likely to contain one or more text encoding errors, by dividing the first word into n-grams of length 2 or more. For each of the plurality of n-grams, a database is queried to determine a respective probability of the n-gram appearing in each of a plurality of recognized languages, and upon determining that the determined probabilities of two consecutive n-grams are each less than a predefined threshold probability, the first word is added to a list of words that likely contain text encoding errors. A confidence level that the first word includes the one or more text encoding errors is calculated, based on a lowest determined probably for the n-grams for the first word.

公开(公告)号：US11699441B2

公开(公告)日：2023-07-11

申请号：US17573014

申请日：2022-01-11

Applicant: Amazon Technologies, Inc.

Inventor： Mark Conrad Kockerbeck ,  Muhammad Yahia ,  Jordan Michael Hughes ,  Kevin Boehm ,  Rohit Sauhta

IPC: G10L15/22 ,  G10L15/30 ,  G10L15/18

CPC classification number: G10L15/22 ,  G10L15/1815 ,  G10L15/30 ,  G10L2015/223

Abstract: The present disclosure describes techniques for dynamically determining when information is to be output to a user, as well as what information is to be output to a user. A natural language processing system may receive, from a first device, first data representing information to be output at a first point during a skill session. The natural language processing system may also receive, from a second device, second data representing a natural language input. The natural language processing system may determine a skill component is to execute with respect to the natural language input. The natural language processing system may send, to the skill component, second data representing the natural language input. The natural language processing system may receive, from the skill component, an indication that an ongoing first skill session with the second device has reached the first point. After receiving the indication and based at least in part on system usage data associated with at least one user, the natural language processing system may determine third data representing a prompt corresponding to the information and send, to the second device, the third data for output.

公开(公告)号：US10671854B1

公开(公告)日：2020-06-02

申请号：US15948567

申请日：2018-04-09

Applicant: Amazon Technologies, Inc.

Inventor： Hooman Mahyar ,  Muhammad Yahia ,  Harshal Dilip Wanjari

IPC: G06K9/00 ,  G06K9/62 ,  H04N21/234 ,  G06N20/00

Abstract: Systems, methods, and computer-readable media are disclosed for systems and methods for intelligent content rating determination. Example methods include determining presence of a first feature in a first frame of a video using an object recognition algorithm, determining presence of a second feature in an audio file associated with the video using an audio processing algorithm, and determining presence of a third feature in a text file associated with the video using a natural language processing algorithm. Certain embodiments may include generating a predicted content rating for the video using a machine learning model, where the predicted content rating is based at least in part on the first feature, the second feature, and the third feature, and using feedback data for the predicted content rating to retrain the machine learning model.

公开(公告)号：US11308332B1

公开(公告)日：2022-04-19

申请号：US16856744

申请日：2020-04-23

Applicant: Amazon Technologies, Inc.

Inventor： Hooman Mahyar ,  Muhammad Yahia ,  Harshal Dilip Wanjari

IPC: G06K9/00 ,  G06N20/00 ,  H04N21/234 ,  G06K9/62

Abstract: Systems, methods, and computer-readable media are disclosed for systems and methods for intelligent content rating determination. Example methods include determining presence of a first feature in a first frame of a video using an object recognition algorithm, determining presence of a second feature in an audio file associated with the video using an audio processing algorithm, and determining presence of a third feature in a text file associated with the video using a natural language processing algorithm. Certain embodiments may include generating a predicted content rating for the video using a machine learning model, where the predicted content rating is based at least in part on the first feature, the second feature, and the third feature, and using feedback data for the predicted content rating to retrain the machine learning model.

公开(公告)号：US11227592B1

公开(公告)日：2022-01-18

申请号：US16455530

申请日：2019-06-27

Applicant: Amazon Technologies, Inc.

Inventor： Mark Conrad Kockerbeck ,  Muhammad Yahia ,  Jordan Michael Hughes ,  Kevin Boehm ,  Rohit Sauhta

IPC: G10L15/22 ,  G10L15/30 ,  G10L15/18

Abstract: The present disclosure describes techniques for dynamically determining when information is to be output to a user, as well as what information is to be output to a user. A natural language processing system may receive, from a first device, first data representing information to be output at a first point during a skill session. The natural language processing system may also receive, from a second device, second data representing a natural language input. The natural language processing system may determine a skill component is to execute with respect to the natural language input. The natural language processing system may send, to the skill component, second data representing the natural language input. The natural language processing system may receive, from the skill component, an indication that an ongoing first skill session with the second device has reached the first point. After receiving the indication and based at least in part on system usage data associated with at least one user, the natural language processing system may determine third data representing a prompt corresponding to the information and send, to the second device, the third data for output.