公开(公告)号：US10284893B2

公开(公告)日：2019-05-07

申请号：US15644915

申请日：2017-07-10

Applicant: AT&T INTELLECTUAL PROPERTY I, L.P.

Inventor： Suhrid Balakrishnan ,  David Lee Applegate ,  Sumit Chopra ,  Simon Urbanek

IPC: H04H60/32 ,  H04N21/2668 ,  H04N21/24 ,  H04N21/2543 ,  H04N21/442 ,  H04N21/658 ,  H04N21/81 ,  H04N21/25 ,  G06Q30/02 ,  H04N21/433

Abstract: A system that incorporates teachings of the subject disclosure may include, for example, determining identified impressions that are detected from consumption data collected from a group of media processors where the identified impressions represent viewing of selected content and where the consumption data indicates channel tuning events at the group of media processors including changing of channels, applying a ridge regression analysis to the identified impressions to determine a predicted number of target impressions per advertisement slot, and generating a media plan based on a ratio of an advertisement slot cost to the predicted number of target impressions per advertisement slot. Other embodiments are disclosed.

公开(公告)号：US09728183B2

公开(公告)日：2017-08-08

申请号：US14936772

申请日：2015-11-10

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Sumit Chopra ,  Dimitrios Dimitriadis ,  Patrick Haffner

IPC: G10L15/08 ,  G10L15/02 ,  G10L15/16

CPC classification number: G10L15/02 ,  G10L15/08 ,  G10L15/16

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for combining frame and segment level processing, via temporal pooling, for phonetic classification. A frame processor unit receives an input and extracts the time-dependent features from the input. A plurality of pooling interface units generates a plurality of feature vectors based on pooling the time-dependent features and selecting a plurality of time-dependent features according to a plurality of selection strategies. Next, a plurality of segmental classification units generates scores for the feature vectors. Each segmental classification unit (SCU) can be dedicated to a specific pooling interface unit (PIU) to form a PIU-SCU combination. Multiple PIU-SCU combinations can be further combined to form an ensemble of combinations, and the ensemble can be diversified by varying the pooling operations used by the PIU-SCU combinations. Based on the scores, the plurality of segmental classification units selects a class label and returns a result.

公开(公告)号：US09218815B2

公开(公告)日：2015-12-22

申请号：US14551907

申请日：2014-11-24

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Ann K. Syrdal ,  Sumit Chopra ,  Patrick Haffner ,  Taniya Mishra ,  Ilija Zeljkovic ,  Eric Zavesky

IPC: G06K9/00 ,  G10L17/24 ,  G06F21/32

CPC classification number: G10L15/25 ,  G06F21/32 ,  G06F2221/2103 ,  G06K9/00255 ,  G06K9/00281 ,  G06K9/00288 ,  G06K9/00315 ,  G06K9/00335 ,  G10L17/24 ,  G10L21/06

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for performing speaker verification. A system configured to practice the method receives a request to verify a speaker, generates a text challenge that is unique to the request, and, in response to the request, prompts the speaker to utter the text challenge. Then the system records a dynamic image feature of the speaker as the speaker utters the text challenge, and performs speaker verification based on the dynamic image feature and the text challenge. Recording the dynamic image feature of the speaker can include recording video of the speaker while speaking the text challenge. The dynamic feature can include a movement pattern of head, lips, mouth, eyes, and/or eyebrows of the speaker. The dynamic image feature can relate to phonetic content of the speaker speaking the challenge, speech prosody, and the speaker's facial expression responding to content of the challenge.

Abstract translation: 本文公开了用于执行说话者验证的系统，方法和非暂时的计算机可读存储介质。 被配置为实施该方法的系统接收到验证说话者的请求，产生对该请求是唯一的文本挑战，并且响应该请求提示说话者发出文本挑战。 然后当扬声器发出文本挑战时，系统记录扬声器的动态图像特征，并且基于动态图像特征和文本挑战来执行说话者验证。 录制扬声器的动态图像功能可以包括在说出文本挑战时录制扬声器的视频。 动态特征可以包括扬声器的头部，嘴唇，嘴巴，眼睛和/或眉毛的运动模式。 动态图像特征可以涉及讲话者讲话的语音内容，语音韵律以及响应于挑战内容的说话者的面部表情。

公开(公告)号：US09208778B2

公开(公告)日：2015-12-08

申请号：US14537400

申请日：2014-11-10

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Sumit Chopra ,  Dimitrios Dimitriadis ,  Patrick Haffner

IPC: G10L15/08 ,  G10L15/02 ,  G10L15/16

CPC classification number: G10L15/02 ,  G10L15/08 ,  G10L15/16

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for combining frame and segment level processing, via temporal pooling, for phonetic classification. A frame processor unit receives an input and extracts the time-dependent features from the input. A plurality of pooling interface units generates a plurality of feature vectors based on pooling the time-dependent features and selecting a plurality of time-dependent features according to a plurality of selection strategies. Next, a plurality of segmental classification units generates scores for the feature vectors. Each segmental classification unit (SCU) can be dedicated to a specific pooling interface unit (PIU) to form a PIU-SCU combination. Multiple PIU-SCU combinations can be further combined to form an ensemble of combinations, and the ensemble can be diversified by varying the pooling operations used by the PIU-SCU combinations. Based on the scores, the plurality of segmental classification units selects a class label and returns a result.

Abstract translation: 本文公开了用于通过时间池来组合帧和段级处理用于语音分类的系统，方法和非暂时的计算机可读存储介质。 帧处理器单元接收输入并从输入中提取与时间相关的特征。 多个池化接口单元基于集合时间依赖特征并根据多个选择策略选择多个时间相关特征来生成多个特征向量。 接下来，多个分段分类单元生成特征向量的得分。 每个分段分类单元（SCU）可专用于特定的汇聚接口单元（PIU）以形成PIU-SCU组合。 可以进一步组合多个PIU-SCU组合以形成组合的集合，并且可以通过改变PIU-SCU组合使用的合并操作来使集合多样化。 基于分数，多个分段分类单元选择分类标签并返回结果。

公开(公告)号：US20140040176A1

公开(公告)日：2014-02-06

申请号：US14052705

申请日：2013-10-12

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Suhrid Balakrishnan ,  Sumit Chopra

IPC: G06N99/00

CPC classification number: G06N5/027 ,  G06F17/18 ,  G06F17/30979 ,  G06N7/005 ,  G06N99/005 ,  G06Q30/0203 ,  G06Q30/0631

Abstract: Methods, systems, and products adapt recommender systems with pairwise feedback. A pairwise question is posed to a user. A response is received that selects a preference for a pair of items in the pairwise question. A latent factor model is adapted to incorporate the response, and an item is recommended to the user based on the response.

Abstract translation: 方法，系统和产品适应具有成对反馈的推荐系统。 一个成对的问题是向用户提出的。 收到一个响应，选择对成对问题中的一对项目的偏好。 潜在因素模型适用于纳入响应，并且基于响应向用户推荐项目。

公开(公告)号：US20160004690A1

公开(公告)日：2016-01-07

申请号：US14853053

申请日：2015-09-14

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Srinivas BANGALORE ,  Sumit Chopra

IPC: G06F17/28

CPC classification number: G06F17/28

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for learning latent representations for natural language tasks. A system configured to practice the method analyzes, for a first natural language processing task, a first natural language corpus to generate a latent representation for words in the first corpus. Then the system analyzes, for a second natural language processing task, a second natural language corpus having a target word, and predicts a label for the target word based on the latent representation. In one variation, the target word is one or more word such as a rare word and/or a word not encountered in the first natural language corpus. The system can optionally assigning the label to the target word. The system can operate according to a connectionist model that includes a learnable linear mapping that maps each word in the first corpus to a low dimensional latent space.

Abstract translation: 本文公开了用于学习自然语言任务的潜在表示的系统，方法和非暂时的计算机可读存储介质。 一种被配置为练习该方法的系统，分析第一自然语言处理任务中的第一自然语言语料库以产生第一语料库中的单词的潜在表示。 然后，系统针对第二自然语言处理任务分析具有目标词的第二自然语言语料库，并且基于潜在表示来预测目标词的标签。 在一个变体中，目标词是一个或多个单词，例如在第一自然语言语料库中不遇到的罕见单词和/或单词。 系统可以选择将标签分配给目标字。 该系统可以根据连接主义模型来操作，该连接主义模型包括将第一语料库中的每个单词映射到低维空间的可学习的线性映射。