公开(公告)号：US20140092990A1

公开(公告)日：2014-04-03

申请号：US13632998

申请日：2012-10-01

Applicant: GOOGLE INC.

Inventor： Vladimir Vuskovic ,  Dhruv Bakshi ,  Amaury Forgeot d'Arc ,  Christoph Poropatits

IPC: H04N7/12

CPC classification number: H04N5/262 ,  G06F17/30038 ,  G06K9/00718 ,  G06K9/6256 ,  G11B27/031 ,  H04N7/12 ,  H04N21/23424 ,  H04N21/23439 ,  H04N21/25825 ,  H04N21/2668 ,  H04N21/2743 ,  H04N21/4312 ,  H04N21/4355 ,  H04N21/44016 ,  H04N21/4722 ,  H04N21/4756 ,  H04N21/812 ,  H04N21/8126 ,  H04N21/84 ,  H04N21/85403

Abstract: A computing device executing an optimizer analyzes a video. The computing device identifies one or more optimizations for the video based on the analysis. The computing device suggests the one or more optimizations to an entity associated with the video. In response to the entity accepting the one or more optimizations, the computing device implements the one or more optimizations for the video.

Abstract translation: 执行优化器的计算设备分析视频。 计算设备基于分析识别视频的一个或多个优化。 计算设备建议对与视频相关联的实体的一个或多个优化。 响应于接受一个或多个优化的实体，计算设备对视频执行一个或多个优化。

公开(公告)号：US10194096B2

公开(公告)日：2019-01-29

申请号：US14860504

申请日：2015-09-21

Applicant: Google Inc.

Inventor： Vladimir Vuskovic ,  Dhruv Bakshi ,  Amaury Forgeot d'Arc ,  Christoph Poropatits

IPC: H04N5/262 ,  G06K9/62 ,  G06K9/00 ,  G11B27/031 ,  H04N21/2343 ,  H04N21/2668 ,  H04N21/44 ,  H04N21/431 ,  H04N21/234 ,  H04N21/258 ,  H04N21/435 ,  H04N21/81 ,  H04N21/475 ,  H04N21/4722 ,  G06F17/30 ,  H04N21/2743 ,  H04N21/854 ,  H04N21/84 ,  H04N7/12

Abstract: A computing device executing an optimizer analyzes a video. The computing device identifies one or more optimizations for the video based on the analysis, the one or more optimizations pertaining to a modification of original contents of the video. The computing device implements the one or more optimizations for the video.

公开(公告)号：US20180277108A1

公开(公告)日：2018-09-27

申请号：US15466422

申请日：2017-03-22

Applicant: Google Inc.

Inventor： Ibrahim Badr ,  Zaheed Sabur ,  Vladimir Vuskovic ,  Adrian Zumbrunnen ,  Lucas Mirelmann

IPC: G10L15/22 ,  G10L15/18 ,  G06F17/30 ,  G06N3/00

CPC classification number: G10L15/22 ,  G06F16/90335 ,  G06N3/006 ,  G10L15/1815 ,  G10L15/1822 ,  G10L2015/223

Abstract: Methods, apparatus, and computer readable media are described related to automated assistants that proactively incorporate, into human-to-computer dialog sessions, unsolicited content of potential interest to a user. In various implementations, in an existing human-to-computer dialog session between a user and an automated assistant, it may be determined that the automated assistant has responded to all natural language input received from the user. Based on characteristic(s) of the user, information of potential interest to the user or action(s) of potential interest to the user may be identified. Unsolicited content indicative of the information of potential interest to the user or the action(s) may be generated and incorporated by the automated assistant into the existing human-to-computer dialog session. In various implementations, the incorporating may be performed in response to the determining that the automated assistant has responded to all natural language input received from the user during the human-to-computer dialog session.

公开(公告)号：US09865260B1

公开(公告)日：2018-01-09

申请号：US15585363

申请日：2017-05-03

Applicant: Google Inc.

Inventor： Vladimir Vuskovic ,  Stephan Wenger ,  Zineb Ait Bahajji ,  Martin Baeuml ,  Alexandru Dovlecel ,  Gleb Skobeltsyn

IPC: G10L15/22 ,  G10L15/18 ,  G06F17/27

CPC classification number: G06F17/278 ,  G06F17/279 ,  G06F17/2881 ,  G10L15/22

Abstract: Methods, apparatus, and computer readable media are described related to automated assistants that proactively incorporate, into human-to-computer dialog sessions, unsolicited content of potential interest to a user. In various implementations, based on content of an existing human-to-computer dialog session between a user and an automated assistant, an entity mentioned by the user or automated assistant may be identified. Fact(s)s related to the entity or to another entity that is related to the entity may be identified based on entity data contained in database(s). For each of the fact(s), a corresponding measure of potential interest to the user may be determined. Unsolicited natural language content may then be generated that includes one or more of the facts selected based on the corresponding measure(s) of potential interest. The automated assistant may then incorporate the unsolicited content into the existing human-to-computer dialog session or a subsequent human-to-computer dialog session.