公开(公告)号：US08688453B1

公开(公告)日：2014-04-01

申请号：US13037114

申请日：2011-02-28

Applicant: Sachindra Joshi ,  Shantanu Godbole

Inventor： Sachindra Joshi ,  Shantanu Godbole

IPC: G06F17/27 ,  G06F17/21 ,  G10L15/00 ,  G10L15/04 ,  G10L21/00 ,  G10L25/00 ,  G10L15/18 ,  G06F7/00 ,  G06F17/30 ,  G06F17/00 ,  G06F17/20 ,  G06F17/22 ,  G06F17/24 ,  G06F17/25 ,  G06F17/26 ,  G06F17/28

CPC classification number: G10L15/00 ,  G06F17/271 ,  G06F17/2785 ,  G06F17/30743 ,  G10L15/1822

Abstract: According to example configurations, a speech processing system can include a syntactic parser, a word extractor, word extraction rules, and an analyzer. The syntactic parser of the speech processing system parses the utterance to identify syntactic relationships amongst words in the utterance. The word extractor utilizes word extraction rules to identify groupings of related words in the utterance that most likely represent an intended meaning of the utterance. The analyzer in the speech processing system maps each set of the sets of words produced by the word extractor to a respective candidate intent value to produce a list of candidate intent values for the utterance. The analyzer is configured to select, from the list of candidate intent values (i.e., possible intended meanings) of the utterance, a particular candidate intent value as being representative of the intent (i.e., intended meaning) of the utterance.

Abstract translation: 根据示例配置，语音处理系统可以包括语法解析器，字提取器，字提取规则和分析器。 语音处理系统的句法解析器解析话语，以确定话语中的语法关系。 词抽取器利用字提取规则来识别话语中相关词的分组，这最有可能代表话语的意图。 语音处理系统中的分析器将由单词提取器产生的每组单词映射到相应的候选意图值，以产生用于发音的候选意图值的列表。 分析器被配置为从话音的候选意图值列表（即，可能的意图的含义）中选择特定的候选意图值来表示话语的意图（即，意图的意思）。

公开(公告)号：US20090150436A1

公开(公告)日：2009-06-11

申请号：US11953198

申请日：2007-12-10

Applicant: Shantanu Godbole ,  Raghuram Krishnapuram ,  Shourya Roy

Inventor： Shantanu Godbole ,  Raghuram Krishnapuram ,  Shourya Roy

IPC: G06F17/30

CPC classification number: G06F16/355

Abstract: The embodiments of the invention provide a method for the automatic identification of changing subtopics within topics. The method begins by receiving customer satisfaction data having unstructured data objects. Next, the data objects are automatically categorized into pre-defined topics, wherein the pre-defined topics do not change throughout the customer satisfaction analysis. The pre-defined topics can be automatically defined based on a history of customer satisfaction data. Following this, a clustering analysis is automatically performed to identify subtopics of the data objects within the pre-defined topics. The subtopics are more specific than the pre-defined topics, and the subtopics can change. Further, the clustering analysis can include extracting features from the data objects and grouping the features into the subtopics. Each of the subtopics includes features having a predetermined degree of similarity.

Abstract translation: 本发明的实施例提供了一种用于在主题内自动识别不断变化的子主题的方法。 该方法开始于接收具有非结构化数据对象的客户满意度数据。 接下来，数据对象被自动分类为预定义的主题，其中预定义的主题在整个客户满意度分析中不改变。 可以根据客户满意度数据的历史自动定义预定义的主题。 此后，将自动执行聚类分析，以确定预定义主题内的数据对象的子主题。 子主题比预定义的主题更具体，子主题可以更改。 此外，聚类分析可以包括从数据对象中提取特征并将特征分组到子主题中。 每个子主题包括具有预定相似度的特征。

公开(公告)号：US20110251839A1

公开(公告)日：2011-10-13

申请号：US12757580

申请日：2010-04-09

Applicant: Jeffrey M. Achtermann ,  Indrajit Bhattacharya ,  Kevin W. English ,  Shantanu Godbole ,  Ajay K. Gupta ,  Ashish Verma

Inventor： Jeffrey M. Achtermann ,  Indrajit Bhattacharya ,  Kevin W. English ,  Shantanu Godbole ,  Ajay K. Gupta ,  Ashish Verma

IPC: G06F17/27 ,  G06F17/21

CPC classification number: G06F17/27 ,  G06F17/2705 ,  G06F17/271 ,  G06F17/2735 ,  G06F17/277 ,  G06F17/278 ,  G06F17/2785 ,  G06F17/2795 ,  G06F17/28 ,  G06F17/2818

Abstract: Determining synonyms of words in a set of documents. Particularly, when provided with a word or phrase as input, in exemplary embodiments there is afforded the return of a predetermined number of “top” synonym words (or phrases) for an input word (or phrase) in a specific collection of text documents. Further, a user is able to provide ongoing and iterative positive or negative feedback on the returned synonym words, by manually accepting or rejecting such words as the process is underway.

Abstract translation: 确定一组文档中单词的同义词。 特别地，当被提供有一个单词或短语作为输入时，在示例性实施例中，提供在特定的文本文档集合中返回预定数量的用于输入单词（或短语）的预定数量的“顶”同义词（或短语）。 此外，用户能够通过手动接受或拒绝该过程正在进行的诸如此类的单词来为所返回的同义词提供持续且迭代的正或负反馈。

公开(公告)号：US20100332424A1

公开(公告)日：2010-12-30

申请号：US12494399

申请日：2009-06-30

Applicant: Indrajit Bhattacharya ,  Tanveer A. Faruquie ,  Shantanu Godbole ,  Mukesh K. Mohania ,  Ullas B. Nambiar

Inventor： Indrajit Bhattacharya ,  Tanveer A. Faruquie ,  Shantanu Godbole ,  Mukesh K. Mohania ,  Ullas B. Nambiar

IPC: G06F15/18 ,  G06N5/02

CPC classification number: G06N5/02

Abstract: Techniques for identifying one or more inconsistencies between an unstructured document and a back-end fact-base are provided. The techniques include automatically parsing a query document and comparing the document with a back-end fact-base comprising facts relevant to the document, identifying one or more inconsistencies between information mentioned in the document and the facts stored in the back-end fact-base, and providing a response to the query document, wherein the response additionally includes the one or more identified inconsistencies.

Abstract translation: 提供了用于识别非结构化文档和后端事实库之间的一个或多个不一致性的技术。 这些技术包括自动解析查询文档并将文档与包含与该文档相关的事实的后端事实基础进行比较，识别文档中提及的信息与存储在后端事实库中的事实之间的一个或多个不一致 并且向所述查询文档提供响应，其中所述响应另外包括所述一个或多个所识别的不一致性。

公开(公告)号：US08370275B2

公开(公告)日：2013-02-05

申请号：US12494399

申请日：2009-06-30

Applicant: Indrajit Bhattacharya ,  Tanveer Afzal Faruquie ,  Shantanu Godbole ,  Mukesh Kumar Mohania ,  Ullas Balan Nambiar

Inventor： Indrajit Bhattacharya ,  Tanveer Afzal Faruquie ,  Shantanu Godbole ,  Mukesh Kumar Mohania ,  Ullas Balan Nambiar

IPC: G06F17/27 ,  G06F17/30 ,  G06F17/21

CPC classification number: G06N5/02

Abstract: Techniques for identifying one or more inconsistencies between an unstructured document and a back-end fact-base are provided. The techniques include automatically parsing a query document and comparing the document with a back-end fact-base comprising facts relevant to the document, identifying one or more inconsistencies between information mentioned in the document and the facts stored in the back-end fact-base, and providing a response to the query document, wherein the response additionally includes the one or more identified inconsistencies.

Abstract translation: 提供了用于识别非结构化文档和后端事实库之间的一个或多个不一致性的技术。 这些技术包括自动解析查询文档并将文档与包含与该文档相关的事实的后端事实基础进行比较，识别文档中提及的信息与存储在后端事实库中的事实之间的一个或多个不一致 并且向所述查询文档提供响应，其中所述响应另外包括所述一个或多个所识别的不一致性。