公开(公告)号：WO2014143885A3

公开(公告)日：2014-09-18

申请号：PCT/US2014/028046

申请日：2014-03-14

Applicant: GOOGLE INC.

Inventor： ZOMET, Asaf ,  CHECHIK, Gal ,  SHYNAR, Michael

IPC: G06F17/30 ,  G06F17/28

Abstract: A device is configured to receive a translation query that requests a translation of terms from a source language to a target language; determine translation features associated with the translation query; assign a feature value to each of the translation features to form feature values; apply a feature weight to each of the feature values to generate a final value; and determine whether to provide a dialog translation user interface or a non-dialog translation user interface based on whether the final value satisfies a threshold. The dialog translation user interface may facilitate translation of a conversation, the non-dialog translation user interface may provide translation search results, and the non-dialog translation user interface may be different than the dialog translation user interface. The device also configured to provide the dialog translation user interface for display when the final value satisfies the threshold

公开(公告)号：WO2010105089A1

公开(公告)日：2010-09-16

申请号：PCT/US2010/027031

申请日：2010-03-11

Applicant: GOOGLE INC. ,  LYON, Richard, F. ,  REHN, Martin ,  WALTERS, Thomas ,  BENGIO, Samy ,  CHECHIK, Gal

Inventor： LYON, Richard, F. ,  REHN, Martin ,  WALTERS, Thomas ,  BENGIO, Samy ,  CHECHIK, Gal

IPC: G10L11/00 ,  G06F17/30

CPC classification number: G10L25/48 ,  G06F17/30743

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, are provided for using audio features to classify audio for information retrieval. In general, one aspect of the subject matter described in this specification can be embodied in methods that include the actions of generating a collection of auditory images, each auditory image being generated from respective audio files according to an auditory model; extracting sparse features from each auditory image in the collection to generate a sparse feature vector representing the corresponding audio file; and ranking the audio files in response to a query including one or more words using the sparse feature vectors and a matching function relating sparse feature vectors to words in the query.

Abstract translation: 提供方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于使用音频特征来分类用于信息检索的音频。 通常，本说明书中描述的主题的一个方面可以体现在包括产生听觉图像的集合的动作的方法中，每个听觉图像根据听觉模型从各个音频文件生成; 从集合中的每个听觉图像中提取稀疏特征以生成表示相应音频文件的稀疏特征向量; 并且响应于包括使用稀疏特征向量的一个或多个单词的查询和将稀疏特征向量与查询中的单词相关联的匹配函数进行排序。

公开(公告)号：WO2014040082A1

公开(公告)日：2014-03-13

申请号：PCT/US2013/059091

申请日：2013-09-10

Applicant: GOOGLE INC.

Inventor： SHYNAR, Michael ,  ZOMET, Asaf ,  CHECHIK, Gal

IPC: H04N21/442

CPC classification number: G11B27/031 ,  H04N5/76 ,  H04N5/765 ,  H04N9/8205 ,  H04N9/87 ,  H04N21/252 ,  H04N21/8549

Abstract: Techniques for summarizing media are described. A viewer-interaction analyzer receives a media file containing media, the media file including a plurality of segments. A segment of the media file is scored based on interactions of a set of raters. Viewer metrics on the segment of the media file are measured based on interactions with the segment of the media file by a set of viewers. A set of feature vectors are formed based on the measured viewer interactions, where feature vectors in the set of feature vectors are based on interactions of the set of viewers. A model is trained based on the set of feature vectors and the score assigned to the segment of the media file.

Abstract translation: 描述用于总结介质的技术。 观众交互分析器接收包含媒体的媒体文件，该媒体文件包括多个片段。 基于一组评估者的相互作用对媒体文件的一部分进行评分。 媒体文件片段上的观看者指标是根据一组观众与媒体文件片段的互动进行衡量的。 基于测量的观看者交互形成一组特征向量，其中特征向量集合中的特征向量基于观看者集合的交互。 基于特征向量集合和分配给媒体文件段的分数训练模型。

公开(公告)号：WO2011025701A1

公开(公告)日：2011-03-03

申请号：PCT/US2010/045909

申请日：2010-08-18

Applicant: GOOGLE INC. ,  CHECHIK, Gal ,  BENGIO, Samy

Inventor： CHECHIK, Gal ,  BENGIO, Samy

IPC: G06K9/62

CPC classification number: G06F17/3082 ,  G06F17/30781 ,  G06F17/30784 ,  G06F17/30817 ,  G06F17/30837 ,  G06F17/30849

Abstract: A system, computer readable storage medium, and computer-implemented method presents video search results responsive to a user keyword query. The video hosting system uses a machine learning process to learn a feature-keyword model associating features of media content from a labeled training dataset with keywords descriptive of their content. The system uses the learned model to provide video search results relevant to a keyword query based on features found in the videos. Furthermore, the system determines and presents one or more thumbnail images representative of the video using the learned model.

Abstract translation: 系统，计算机可读存储介质和计算机实现的方法响应于用户关键词查询呈现视频搜索结果。 视频托管系统使用机器学习过程来学习将标记训练数据集中的媒体内容的特征与描述其内容的关键字相关联的特征关键字模型。 该系统使用学习模型，根据视频中的功能提供与关键字查询相关的视频搜索结果。 此外，系统使用所学习的模型来确定并呈现代表视频的一个或多个缩略图。

公开(公告)号：EP3090358A1

公开(公告)日：2016-11-09

申请号：EP14822012.2

申请日：2014-12-15

Applicant: Google Inc.

Inventor： CHECHIK, Gal ,  SEGALIS, Eyal ,  LEVIATHAN, Yaniv ,  TZUR, Yoav

IPC: G06F17/30

CPC classification number: G06F17/30867 ,  G06F17/30265 ,  G06F17/3053 ,  G06F17/30646 ,  G06F17/30654 ,  G06F17/30864

Abstract: Methods and systems for providing rich content with an answer to a question query. A method includes receiving a query determined to be a question query and a corresponding answer generated in response to the question query, generating a contextual query that includes an element relating to the question query and an element relating to the answer; submitting the contextual query to a rich content search process and receiving data specifying a first set of rich content items responsive to the contextual query, determining first rich content item in the first set of rich content items that meet a context condition that is indicative of a rich content item providing contextual information of both elements of the question query and the answer query; and preferentially selecting from the first content items relative to the second rich content items to be provided as one or more answer rich content items.

公开(公告)号：EP2471026A1

公开(公告)日：2012-07-04

申请号：EP10812505.5

申请日：2010-08-18

Applicant: Google Inc.

Inventor： CHECHIK, Gal ,  BENGIO, Samy

IPC: G06K9/62

CPC classification number: G06F17/3082 ,  G06F17/30781 ,  G06F17/30784 ,  G06F17/30817 ,  G06F17/30837 ,  G06F17/30849

Abstract: A system, computer readable storage medium, and computer-implemented method presents video search results responsive to a user keyword query. The video hosting system uses a machine learning process to learn a feature-keyword model associating features of media content from a labeled training dataset with keywords descriptive of their content. The system uses the learned model to provide video search results relevant to a keyword query based on features found in the videos. Furthermore, the system determines and presents one or more thumbnail images representative of the video using the learned model.

公开(公告)号：WO2014105697A1

公开(公告)日：2014-07-03

申请号：PCT/US2013/076907

申请日：2013-12-20

Applicant: GOOGLE INC.

Inventor： CHECHIK, Gal ,  ZOMET, Asaf ,  SHYNAR, Michael

IPC: G06F3/0488 ,  G06F17/30

CPC classification number: G06F17/3064 ,  G06F3/04883

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying a query for selected content. In one aspect, a method includes receiving gesture data specifying a user gesture interacting with a portion of displayed content. A subset of the content is identified based on the gesture data. A set of candidate search queries is identified based on the subset of the content. A likelihood score is determined for each candidate search query. The likelihood score for a candidate search query indicates a likelihood that the candidate search query is an intended search query specified by the user gesture. The likelihood score for each candidate search query is adjusted using a normalization factor. The normalization factor can be based on a number of characters included in the candidate search query. One or more of the candidate search queries are selected based on the adjusted likelihood scores.

Abstract translation: 方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于识别所选内容的查询。 一方面，一种方法包括接收指定与所显示内容的一部分交互的用户手势的手势数据。 基于手势数据识别内容的子集。 基于内容的子集来识别一组候选搜索查询。 确定每个候选搜索查询的似然分数。 候选搜索查询的似然分数指示候选搜索查询是由用户手势指定的预期搜索查询的可能性。 使用归一化因子调整每个候选搜索查询的似然分数。 归一化因子可以基于候选搜索查询中包括的多个字符。 基于经调整的似然分数来选择一个或多个候选搜索查询。

公开(公告)号：WO2014089089A1

公开(公告)日：2014-06-12

申请号：PCT/US2013/072885

申请日：2013-12-03

Applicant: GOOGLE INC.

Inventor： ZOMET, Asaf ,  SHYNAR, Michael ,  KEYSAR, Dvir ,  CHECHIK, Gal

IPC: G06F17/00 ,  G06F17/30

CPC classification number: G06Q30/0629

Abstract: Systems and methods are described herein for comparing products in a marketplace. An image or video of the products may be captured using a camera associated with a mobile device. User input may be received to select two or more products within the image. Machine vision techniques may be applied to specifically identify the selected products. Product features associated with each of the identified products may be retrieved and formatted into a comparison of product features. The comparison may be presented to the user.

Abstract translation: 这里描述了用于比较市场中的产品的系统和方法。 可以使用与移动设备相关联的摄像机来捕获产品的图像或视频。 可以接收用户输入以选择图像内的两个或更多个产品。 可以应用机器视觉技术来具体识别所选择的产品。 与每个识别的产品相关联的产品特征可以被检索和格式化成产品特征的比较。 该比较可以呈现给用户。

公开(公告)号：EP2939099A1

公开(公告)日：2015-11-04

申请号：EP13821333.5

申请日：2013-12-20

Applicant: Google Inc.

Inventor： CHECHIK, Gal ,  ZOMET, Asaf ,  SHYNAR, Michael

IPC: G06F3/0488 ,  G06F17/30

CPC classification number: G06F17/3064 ,  G06F3/04883

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying a query for selected content. In one aspect, a method includes receiving gesture data specifying a user gesture interacting with a portion of displayed content. A subset of the content is identified based on the gesture data. A set of candidate search queries is identified based on the subset of the content. A likelihood score is determined for each candidate search query. The likelihood score for a candidate search query indicates a likelihood that the candidate search query is an intended search query specified by the user gesture. The likelihood score for each candidate search query is adjusted using a normalization factor. The normalization factor can be based on a number of characters included in the candidate search query. One or more of the candidate search queries are selected based on the adjusted likelihood scores.

公开(公告)号：EP2406787B1

公开(公告)日：2014-05-14

申请号：EP10712602.1

申请日：2010-03-11

Applicant: Google Inc.

Inventor： LYON, Richard, F. ,  REHN, Martin ,  WALTERS, Thomas ,  BENGIO, Samy ,  CHECHIK, Gal

IPC: G10L25/48 ,  G06F17/30

CPC classification number: G10L25/48 ,  G06F17/30743