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    • 41. 发明授权
    • Method and apparatus for organizing and optimizing content in dialog systems
    • 用于组织和优化对话系统内容的方法和装置
    • US09201923B2
    • 2015-12-01
    • US11243599
    • 2005-10-04
    • Fuliang WengHeather Pon-Barry
    • Fuliang WengHeather Pon-Barry
    • G06F17/30
    • G06F17/30401G06F17/3064G06F17/30646G06F17/30654G06F17/30672G06F17/30976G06F17/30979G10L2015/221
    • Embodiments of a configurable content optimizer for use in dialog systems are described. In one embodiment, the content optimizer is a configurable component that acts as an intermediary between a dialog management module and a knowledge management module of a dialog system during the query process. The content optimizer module makes extensive use of the system ontology and organizes items returned by the knowledge base and makes adjustments to the query so that a reasonable number of responses are returned. Each query is broken down into a number of constraints, the constraints are characterized by type, and adjustments are made by strategies that include relaxing or tightening constraints in the query. Generic strategies for the potential adjustments are represented in a configurable manner so that the content optimizing module can be easily applied to new domains.
    • 描述在对话系统中使用的可配置内容优化器的实施例。 在一个实施例中,内容优化器是在查询过程期间充当对话系统的对话管理模块和知识管理模块之间的中介的可配置组件。 内容优化器模块广泛使用系统本体并组织知识库返回的项目,并对查询进行调整,以便返回合理数量的响应。 每个查询被分解成许多约束,约束由类型表征,并且通过包括在查询中放松或紧缩约束的策略进行调整。 潜在调整的通用策略以可配置的方式表示,使内容优化模块可以轻松应用于新域。
    • 49. 发明授权
    • System and method for detecting repeated patterns in dialog systems
    • 用于检测对话系统中重复模式的系统和方法
    • US08140330B2
    • 2012-03-20
    • US12139401
    • 2008-06-13
    • Mert CevikFuliang Weng
    • Mert CevikFuliang Weng
    • G10L15/00G10L15/04G10L15/10G10L15/12
    • G10L15/22G10L15/12
    • Embodiments of a method and system for detecting repeated patterns in dialog systems are described. The system includes a dynamic time warping (DTW) based pattern comparison algorithm that is used to find the best matching parts between a correction utterance and an original utterance. Reference patterns are generated from the correction utterance by an unsupervised segmentation scheme. No significant information about the position of the repeated parts in the correction utterance is assumed, as each reference pattern is compared with the original utterance from the beginning of the utterance to the end. A pattern comparison process with DTW is executed without knowledge of fixed end-points. A recursive DTW computation is executed to find the best matching parts that are considered as the repeated parts as well as the end-points of the utterance.
    • 描述用于检测对话系统中的重复模式的方法和系统的实施例。 该系统包括基于动态时间扭曲(DTW)的模式比较算法,用于在校正发声和原始话语之间找到最佳匹配部分。 通过无监督分割方案从校正发声产生参考模式。 假设在校正发声中重复部分的位置的重要信息,因为每个参考图案与从话语开始到结束的原始话语进行比较。 在不知道固定端点的情况下执行DTW的模式比较过程。 执行递归DTW计算,以找到被认为是重复部分以及话语终点的最佳匹配部分。
    • 50. 发明申请
    • System and Method for Detecting Repeated Patterns in Dialog Systems
    • 用于检测对话系统中重复模式的系统和方法
    • US20090313016A1
    • 2009-12-17
    • US12139401
    • 2008-06-13
    • Mert CevikFuliang Weng
    • Mert CevikFuliang Weng
    • G10L15/00
    • G10L15/22G10L15/12
    • Embodiments of a method and system for detecting repeated patterns in dialog systems are described. The system includes a dynamic time warping (DTW) based pattern comparison algorithm that is used to find the best matching parts between a correction utterance and an original utterance. Reference patterns are generated from the correction utterance by an unsupervised segmentation scheme. No significant information about the position of the repeated parts in the correction utterance is assumed, as each reference pattern is compared with the original utterance from the beginning of the utterance to the end. A pattern comparison process with DTW is executed without knowledge of fixed end-points. A recursive DTW computation is executed to find the best matching parts that are considered as the repeated parts as well as the end-points of the utterance.
    • 描述用于检测对话系统中的重复模式的方法和系统的实施例。 该系统包括基于动态时间扭曲(DTW)的模式比较算法,用于在校正发声和原始话语之间找到最佳匹配部分。 通过无监督分割方案从校正发声产生参考模式。 假设在校正发声中重复部分的位置的重要信息,因为每个参考图案与从话语开始到结束的原始话语进行比较。 在不知道固定端点的情况下执行DTW的模式比较过程。 执行递归DTW计算,以找到被认为是重复部分以及话语终点的最佳匹配部分。