公开(公告)号：US20140136508A1

公开(公告)日：2014-05-15

申请号：US13673917

申请日：2012-11-09

申请人： PALO ALTO RESEARCH CENTER INCORPORATED

发明人： Kristian Lyngbaek ,  Lester D. Nelson ,  Eric A. Bier ,  Margaret H. Szymanski

IPC分类号： G06F17/30

CPC分类号： G06F16/9566

摘要： A system and method for providing Web site navigation recommendations is provided. A Web page of interest is identified as a destination Web page. A domain of Web pages related to the destination Web page is determined. Information is extracted from each Web page in the domain and a recommendation comprising instructions for navigating to the destination Web page is generated based on the extracted information.

摘要翻译： 提供了一种用于提供网站导航建议的系统和方法。 感兴趣的网页被标识为目标网页。 确定与目标网页相关的网页域。 从域中的每个网页提取信息，并且基于所提取的信息生成包括用于导航到目的地网页的指令的推荐。

公开(公告)号：US20230325453A1

公开(公告)日：2023-10-12

申请号：US18209269

申请日：2023-06-13

申请人： PALO ALTO RESEARCH CENTER INCORPORATED

发明人： Kristian Lyngbaek ,  Lester D. Nelson ,  Eric A. Bier ,  Margaret H. Szymanski

IPC分类号： G06F16/955

CPC分类号： G06F16/9566

摘要： A system and method for providing Website navigation recommendations is provided. A Web page of interest is identified as a destination Web page. A domain of Web pages related to the destination Web page is determined. Information is extracted from each Web page in the domain and a recommendation comprising instructions for navigating to the destination Web page is generated based on the extracted information.

公开(公告)号：US20180113854A1

公开(公告)日：2018-04-26

申请号：US15332766

申请日：2016-10-24

申请人： Palo Alto Research Center Incorporated

发明人： Jesse Vig ,  Harish Arsikere ,  Margaret H. Szymanski ,  Luke R. Plurkowski ,  Kyle D. Dent ,  Daniel G. Bobrow ,  Daniel Davies ,  Eric Saund

IPC分类号： G06F17/27 ,  G10L15/02 ,  G10L15/18 ,  G10L25/90 ,  G10L25/87 ,  G10L25/63 ,  H04M3/51

CPC分类号： G06F17/279 ,  G06F17/277 ,  G10L15/26 ,  G10L25/48 ,  H04M3/51 ,  H04M2201/40 ,  H04M2203/357

摘要： Embodiments of the present invention provide a system for automatically extracting conversational structure from a voice record based on lexical and acoustic features. The system also aggregates business-relevant statistics and entities from a collection of spoken conversations. The system may infer a coarse-level conversational structure based on fine-level activities identified from extracted acoustic features. The system improves significantly over previous systems by extracting structure based on lexical and acoustic features. This enables extracting conversational structure on a larger scale and finer level of detail than previous systems, and can feed an analytics and business intelligence platform, e.g. for customer service phone calls. During operation, the system obtains a voice record. The system then extracts a lexical feature using automatic speech recognition (ASR). The system extracts an acoustic feature. The system then determines, via machine learning and based on the extracted lexical and acoustic features, a coarse-level structure of the conversation.

公开(公告)号：US20210287664A1

公开(公告)日：2021-09-16

申请号：US16817944

申请日：2020-03-13

申请人： Palo Alto Research Center Incorporated

发明人： Evgeniy Bart ,  Margaret H. Szymanski

IPC分类号： G10L15/14 ,  G06N20/00 ,  G06N3/08

摘要： Digitized media is received that records a conversation between individuals. Cues are extracted from the digitized media that indicate properties of the conversation. The cues are entered as training data into a machine learning module to create a trained machine learning model. The trained machine learning model is used in a processor to detect other misalignments in subsequent digitized conversations.

公开(公告)号：US20140046665A1

公开(公告)日：2014-02-13

申请号：US14058178

申请日：2013-10-18

申请人： Palo Alto Research Center Incorporated

发明人： Paul M. Aoki ,  Margaret H. Szymanski ,  James Thornton ,  Daniel H. Wilson ,  Allison G. Woodruff

IPC分类号： G10L17/00

CPC分类号： G10L17/005 ,  G10L15/18 ,  G10L21/0208 ,  G10L25/78 ,  G10L2015/088 ,  H04M3/564 ,  H04M3/566 ,  H04M3/568 ,  H04M3/569

摘要： A system and method for enhancing visual representation to individuals participating in a conversation is provided. Visual data for a plurality of individuals participating in one or more conversations is analyzed. Possible conversational configurations of the individuals are generated. Each possible conversational configuration includes one or more pair-wise probabilities of at least two of the individuals. A probability weight is assigned to each of the pair-wise probabilities having a likelihood that the individuals of that pair-wise probability are participating in a conversation. A probability of each possible conversational configuration is determined by combining the probability weights for the pair-wise probabilities of that possible conversational configuration. The possible conversational configuration with the highest probability is selected as a most probable configuration. The individuals participating in the conversations based on the pair-wise probabilities with the most probable configuration are determined. Visual representation is enhanced for each individual participating in the determined conversations.

摘要翻译： 提供了一种用于增强参与对话的个人的视觉表示的系统和方法。 分析参与一个或多个对话的多个个体的视觉数据。 生成个人的可能会话配置。 每个可能的对话配置包括至少两个个体的一个或多个成对概率。 将概率权重分配给具有成对概率的个人参与会话的可能性的成对概率中的每一个。 通过组合可能的会话配置的成对概率的概率权重来确定每个可能的会话配置的概率。 选择具有最高概率的可能对话配置作为最可能的配置。 基于具有最可能配置的成对概率参与对话的个体被确定。 对于参与确定的对话的每个人，视觉表示被增强。

公开(公告)号：US11817086B2

公开(公告)日：2023-11-14

申请号：US16817944

申请日：2020-03-13

申请人： Palo Alto Research Center Incorporated

发明人： Evgeniy Bart ,  Margaret H. Szymanski

IPC分类号： G06N3/08 ,  G10L15/14 ,  G06N20/00 ,  G10L15/06 ,  G06F16/28 ,  G10L17/26

CPC分类号： G10L15/144 ,  G06N3/08 ,  G06N20/00 ,  G06F16/285 ,  G06F2203/011 ,  G10L17/26 ,  G10L2015/0631

摘要： Digitized media is received that records a conversation between individuals. Cues are extracted from the digitized media that indicate properties of the conversation. The cues are entered as training data into a machine learning module to create a trained machine learning model. The trained machine learning model is used in a processor to detect other misalignments in subsequent digitized conversations.

公开(公告)号：US10592611B2

公开(公告)日：2020-03-17

申请号：US15332766

申请日：2016-10-24

申请人： Palo Alto Research Center Incorporated

发明人： Jesse Vig ,  Harish Arsikere ,  Margaret H. Szymanski ,  Luke R. Plurkowski ,  Kyle D. Dent ,  Daniel G. Bobrow ,  Daniel Davies ,  Eric Saund

IPC分类号： G10L15/00 ,  G06F17/27 ,  G10L25/48 ,  G10L15/26 ,  H04M3/51

摘要： Embodiments of the present invention provide a system for automatically extracting conversational structure from a voice record based on lexical and acoustic features. The system also aggregates business-relevant statistics and entities from a collection of spoken conversations. The system may infer a coarse-level conversational structure based on fine-level activities identified from extracted acoustic features. The system improves significantly over previous systems by extracting structure based on lexical and acoustic features. This enables extracting conversational structure on a larger scale and finer level of detail than previous systems, and can feed an analytics and business intelligence platform, e.g. for customer service phone calls. During operation, the system obtains a voice record. The system then extracts a lexical feature using automatic speech recognition (ASR). The system extracts an acoustic feature. The system then determines, via machine learning and based on the extracted lexical and acoustic features, a coarse-level structure of the conversation.