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公开(公告)号：US20050086592A1
公开(公告)日：2005-04-21
申请号：US10684508
申请日：2003-10-15
申请人： Livia Polanyi , Martin Van Den Berg , Giovanni Thione , Richard Crouch , Christopher Culy , David Ahn
发明人： Livia Polanyi , Martin Van Den Berg , Giovanni Thione , Richard Crouch , Christopher Culy , David Ahn
CPC分类号： G06F17/279 , G06F17/30719 , Y10S707/99931 , Y10S707/99933 , Y10S707/99936
摘要： Techniques are provided for segmenting text into categorized discourse constituents and attaching discourse constituents into a structural representation of discourse. Techniques for determining hybrid structural and non-structural summaries of a text are also provided. A text is segmented based on a theory of discourse analysis into at least a main discourse constituent containing spatio-temporal information about a single event in a possible world view. The discourse constituents are then inserted into a structural representation of discourse. Non-structural techniques are used to determine relevance scores and important discourse constituents are determined. Relevance scores are percolated through the structural representation of discourse to determine supporting preceding discourse constituents that preserve grammaticality. A hybrid text summary is then determined based on the structural representation of the discourse and relevance scores.
摘要翻译： 提供了将文本分割成分类话语组成部分并将话语组成部分附加到话语的结构表示中的技术。 还提供了用于确定文本的混合结构和非结构摘要的技术。 基于话语分析理论将文本分割成至少包含可能的世界观中关于单个事件的时空信息的主要话语成分。 话语成分然后插入话语的结构表示。 非结构性技术用于确定相关性分数，确定重要的话语成分。 相关性分数通过话语的结构表示来抵消，以确定支持保留语法的前面的话语组成部分。 然后基于话语和相关性分数的结构表示来确定混合文本摘要。
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2.发明申请Systems and methods for determining relevant information based on document structure 有权基于文件结构确定相关信息的系统和方法公开(公告)号：US20070143098A1
公开(公告)日：2007-06-21
申请号：US11301853
申请日：2005-12-12
申请人： Martin Van Den Berg , Giovanni Thione , Livia Polanyi , Eleanor Rieffel , Patrick Chiu , Bee Liew
发明人： Martin Van Den Berg , Giovanni Thione , Livia Polanyi , Eleanor Rieffel , Patrick Chiu , Bee Liew
IPC分类号： G06F17/20
CPC分类号： G06F17/279
摘要： Techniques are provided for determining relevant information from a document based on document structure. A document is selected and structural elements within the document having a dominance relationship are determined. A first location within the document is selected. The structural element surrounding the first location is determined and the surrounding and non-surrounding structural elements are characterized. Additional documents are associated with the first location in the surrounding structural element based on the surrounding structural element characterization and the non-surrounding structural element characterization. Techniques for dynamically determining annotations for images based on document structure are also provided.
摘要翻译： 提供了基于文档结构从文档确定相关信息的技术。 选择文档并且确定具有优势关系的文档内的结构元素。 选择文档中的第一个位置。 确定围绕第一位置的结构元件，并且对周围和非周围结构元件进行表征。 基于周围结构元素表征和非周围结构元素表征，附加文档与周围结构元件中的第一位置相关联。 还提供了用于动态地确定基于文档结构的图像注释的技术。
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公开(公告)号：US20050182618A1
公开(公告)日：2005-08-18
申请号：US10807009
申请日：2004-03-23
CPC分类号： G06F17/279
摘要： Techniques are provided for determining and using interaction models. Discourse functions, prosodic features and turn information are determined from the speech information in a training corpus. Statistics, decision trees, rules and/or various other methods are used to determine a predictive interaction model based on the discourse functions, the prosodic features and the turn information. Predictive interaction models are optionally determined for individual users, genres, languages and/or other characteristics of the speech information. The predictive interaction model is useable to predict turns in a dialogue based on the discourse functions and prosodic features identified in the speech information. Speech information is presented and/or received based on the predictive interaction model.
摘要翻译： 提供了确定和使用交互模型的技术。 话语功能，韵律特征和转向信息由训练语料库中的语音信息确定。 统计学，决策树，规则和/或各种其他方法被用于基于话语功能，韵律特征和转向信息来确定预测交互模型。 可选地针对个人用户，流派，语言和/或语音信息的其他特征来确定预测交互模型。 预测交互模型可用于基于语音信息中识别的话语功能和韵律特征来预测对话中的转折。 基于预测交互模型呈现和/或接收语音信息。
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4.发明申请公开(公告)号：US20050182625A1
公开(公告)日：2005-08-18
申请号：US10781443
申请日：2004-02-18
CPC分类号： G06F17/279
摘要： Techniques are provided for determining predictive models of discourse functions based on prosodic features of natural language speech. Inter and intra sentential discourse functions in a training corpus of natural language speech utterances are determined. The discourse functions are clustered. The exemplary prosodic features associated with each type of discourse function are determined. Machine learning, observation and the like are used to determine a subset of prosodic features associated with each type of discourse function useful in predicting the likelihood of each type of discourse function.
摘要翻译： 提供了基于自然语言语言韵律特征来确定话语功能的预测模型的技术。 确定自然语言言语言训练语料库中的内部和内部话语功能。 话语功能是聚类的。 确定与各种话语功能相关联的示范性韵律特征。 机器学习，观察等用于确定与预测每种类型的话语功能的可能性有用的每种类型的话语功能相关联的韵律特征的子集。
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5.发明申请Systems and methods for synthesizing speech using discourse function level prosodic features 审中-公开使用话语功能级韵律特征合成语音的系统和方法公开(公告)号：US20050187772A1
公开(公告)日：2005-08-25
申请号：US10785199
申请日：2004-02-25
CPC分类号： G10L13/10
摘要： Techniques are provided for synthesizing speech using discourse function level prosodic features. An output text is determined. The discourse functions within the text are determined based on a theory of discourse analysis such as the Unified Linguistic Discourse Model. The salient prosodic features associated with the discourse functions are identified using a predictive model of discourse functions or some other model of salient prosodic features. The discourse functions are transformed into synthesized speech. Discourse function level prosodic feature adjustments are determined and applied to the synthesized speech is output.
摘要翻译： 提供了使用话语功能级韵律特征来合成语音的技术。 确定输出文本。 文本中的话语功能是基于话语分析理论（如统一语言话语模型）来确定的。 与话语功能相关的突出韵律特征使用话语功能的预测模型或其他一些显着的韵律特征模型进行识别。 话语功能被转化为合成语音。 话语功能水平韵律特征调整被确定并应用于合成语音输出。
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公开(公告)号：US20050182619A1
公开(公告)日：2005-08-18
申请号：US10807532
申请日：2004-03-23
CPC分类号： G06F17/279
摘要： Techniques are provided for resolving ambiguity in natural language speech. Speech is recognized using automatic speech recognition. A theory of discourse analysis is determined and at least one set of candidate discourse functions is determined based on the theory of discourse analysis. Prosodic features in the speech and a correlation between the prosodic features and the discourse functions is determined. The sets of candidate discourse functions are ranked based on the prosodic features in the speech information and a correlation to the prosodic features expected for the determined discourse functions. Ambiguity is resolved between sets of candidate discourse functions based on the rank information.
摘要翻译： 提供了解决自然语言语言歧义的技巧。 使用自动语音识别识别语音。 确定话语分析理论，并根据话语分析理论确定至少一组候选话语功能。 言语中的韵律特征以及韵律特征与话语功能之间的相关性被确定。 基于语音信息中的韵律特征和与确定的话语功能预期的韵律特征的相关性，对候选语篇功能的集合进行排序。 基于等级信息来解决候选话语功能集之间的歧义。
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公开(公告)号：US20070073533A1
公开(公告)日：2007-03-29
申请号：US11405385
申请日：2006-04-17
IPC分类号： G06F17/27
CPC分类号： G06F17/279
摘要： A structural natural language index is created by segmenting documents within a repository into text portions and extracting named entity, co-reference, lexical entries, structural-semantic relationships, speaker attribution and meronymic derived features. A constituent structure is determined that contains the constituent elements and ordering information sufficient to reconstruct the text portion. A functional structure of the text portions is determined. A set of characterizing predicative triples are formed from the functional structure by applying linearization transfer rules. The constituent structure, the characterizing predicative triples and the derived features are combined to form a canonical form of the text portion. Each canonical form is added to the structural natural language index. A retrieved question is classified to determine question type and a corresponding canonical form for the question is generated. The entries in the structural natural language index are searched for entries matching the canonical form of the question and relevant to the question type. The characterizing predicative triples are used in conjunction with a generation grammar to create an answer. If the generation fails, some or all of the constituent structure of the matching entry is returned as the answer.
摘要翻译： 通过将仓库内的文档分割成文本部分并提取命名实体，共同参考，词汇条目，结构语义关系，说话者归属和meronymic派生特征来创建结构自然语言索引。 确定包含足以重建文本部分的组成元素和排序信息的组成结构。 确定文本部分的功能结构。 通过应用线性化转移规则，从功能结构形成一组表征性谓词三元组。 组合结构，特征谓词三元组和派生特征被组合形成文本部分的规范形式。 每个规范形式被添加到结构自然语言指数。 检索到的问题被分类以确定问题类型，并且生成关于问题的相应的规范形式。 搜索结构自然语言索引中的条目，以匹配问题的规范形式并与问题类型相关的条目。 表征谓词三元组与一代生成语法一起使用以创建答案。 如果生成失败，则返回匹配条目的部分或全部组成结构作为答案。
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公开(公告)号：US20050171926A1
公开(公告)日：2005-08-04
申请号：US10768675
申请日：2004-02-02
IPC分类号： G06F3/16 , G06F7/00 , G06F17/24 , G10L15/00 , G10L15/06 , G10L15/18 , G10L15/22 , G10L15/24 , G10L15/28 , G10L17/00
CPC分类号： G06F17/24 , G10L15/22 , G10L2015/228 , Y10S707/99936
摘要： Techniques are provided for determining collaborative notes and automatically recognizing speech, handwriting and other type of information. Domain and optional actor/speaker information associated with the support information is determined. An initial automatic speech recognition model is determined based on the domain and/or actor information. The domain and/or actor/speaker language model is used to recognize text in the speech information associated with the support information. Presentation support information such as slides, speaker notes and the like are determined. The semantic overlap between the support information and the salient non-function words in the recognized text and collaborative user feedback information are used to determine relevancy scores for the recognized text. Grammaticality, well formedness, self referential integrity and other features are used to determine correctness scores. Suggested collaborative notes are displayed in the user interface based on the salient non-function words. User actions in the user interface determine feedback signals. Recognition models such as automatic speech recognition, handwriting recognition are determined based on the feedback signals and the correctness and relevance scores.
摘要翻译： 提供了用于确定协作笔记并自动识别语音，手写和其他类型的信息的技术。 确定与支持信息相关联的域和可选演员/扬声器信息。 基于域和/或行为者信息确定初始自动语音识别模型。 域和/或演员/扬声器语言模型用于识别与支持信息相关联的语音信息中的文本。 确定幻灯片，说话者笔记等的演示支援信息。 使用识别文本中的支持信息和显着非函数词之间的语义重叠以及协作用户反馈信息来确定识别文本的相关性得分。 使用语法，良好的形态，自我参照完整性等特征来确定正确性分数。 基于显着的非功能词，建议的协作笔记显示在用户界面中。 用户界面中的用户操作决定了反馈信号。 基于反馈信号和正确性和相关性分数确定识别模型，如自动语音识别，手写识别。
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公开(公告)号：US20060233342A1
公开(公告)日：2006-10-19
申请号：US11090824
申请日：2005-03-24
申请人： Giovanni Thione , Martin Den Berg
发明人： Giovanni Thione , Martin Den Berg
IPC分类号： H04M7/00
CPC分类号： G06F17/3089 , H04L12/66
摘要： Techniques are provided to determine service data features from an archive of web service transactions. Data features for functionally identical classes of service are determined. Differentiating data feature patterns uniquely identifying each service within the class are learned using machine learning, clustering, statistical analysis and the like. A service map associating services with the differentiating patterns is determined. The service map contains data feature patterns that differentiate among otherwise functionally identical services. The data features are optionally associated with past usage, objective and subjective service quality measurements and the like. The data features of the received service requests are compared to differentiating patterns in the service map. The service associated with the differentiating patterns matching the data features of the service request is selected. The data features of the service request may include, but document language, document genre, number of words or characters, type of images, subject matter of images and the like.
摘要翻译： 提供技术来从Web服务事务的归档中确定服务数据特征。 确定功能相同的服务类别的数据特征。 使用机器学习，聚类，统计分析等方法，对使用该类别中唯一标识每个服务的数据特征模式进行区分。 确定将服务与区分模式相关联的服务地图。 服务地图包含区分功能相同服务的数据特征模式。 数据特征可选地与过去的使用，客观和主观的服务质量测量等相关联。 将接收的服务请求的数据特征与服务映射中的区分模式进行比较。 选择与匹配服务请求的数据特征的区分模式相关联的服务。 服务请求的数据特征可以包括但是文档语言，文档类型，单词或字符的数量，图像的类型，图像的主题等等。
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公开(公告)号：US20060242687A1
公开(公告)日：2006-10-26
申请号：US11111106
申请日：2005-04-20
申请人： Giovanni Thione , Jonathan Trevor
发明人： Giovanni Thione , Jonathan Trevor
IPC分类号： H04L9/32
CPC分类号： G06F21/34 , G06F21/445
摘要： Techniques are provided for dynamically connecting and transforming user interface events between user and generic devices based on physical keys. A user and a user device are determined. The user device is authenticated based on a login sequence, smartcard or the like. A physical key associated with the user is physically associated with a generic device by insertion, wireless link, proximity, RFID detection and the like. The dynamic association is communicated over a first communications channel. A user device confirms the dynamic association over a second communications channel. The dynamically associated generic device communicates user interface events with the dynamic user interface proxy. The user device also communicates user interface events with the dynamic user interface proxy. The dynamic user interface proxy receives, optionally transforms and routes the user interface events associated with the user device and the generic device. The dynamic user interface proxy routes received user interface events to the respective devices based on the dynamic associations between a user, a user identifier and devices associated with the user's physical key. Inter-modal user interface events are optionally transformed by the dynamic user interface proxy based on internal and/or externally accessible transformation functions.
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