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1. 发明授权

US6092034A Statistical translation system and method for fast sense disambiguation and translation of large corpora using fertility models and sense models 失效
标题翻译：使用生育力模型和感官模型对大型语料库进行快速消歧和翻译的统计翻译系统和方法
公开(公告)号：US6092034A
公开(公告)日：2000-07-18
申请号：US123166
申请日：1998-07-27
申请人： Jeffrey Scott McCarley , Salim Roukos
发明人： Jeffrey Scott McCarley , Salim Roukos
IPC分类号： G06F17/27 , G06F17/28
CPC分类号： G06F17/2795 , G06F17/2818
摘要： A system and method for translating a series of source words in a first language to a series of target words in a second language is provided. The system includes an input device for inputting the series of source words. A fertility hypothesis generator operatively coupled to the input device generates at least one fertility hypotheses for a fertility of a source word, based on the source word and a context of the source word. A sense hypothesis generator operatively coupled to the input device generates sense hypotheses for a translation of the source word, based on the source word and the context of the source word. A fertility model operatively coupled to the fertility hypothesis generator determines a probability of the fertility of the source word, based on the source word and the context of the source word. A sense model operatively coupled to the sense hypothesis generator determines a probability of a target word being a correct translation of the source word, based on the source word and the context of the source word. A decoder operatively coupled to the fertility and sense models for generating a list of target words for the translation of the source word, based on the probability calculated by the fertility model and the probability calculated by the sense model.
摘要翻译：提供了一种用于将第一语言中的一系列源词翻译为第二语言的一系列目标词的系统和方法。该系统包括用于输入一系列源字的输入装置。可操作地耦合到输入装置的生殖力假设发生器基于源字和源字的上下文产生用于源字的生育力的至少一个生育力假设。可操作地耦合到输入设备的感觉假设发生器基于源字和源字的上下文产生用于源字的翻译的有意义假设。有效耦合到生育力假设发生器的生育力模型基于源词和源词的上下文来确定源词的生育力的概率。可操作地耦合到感觉假设发生器的感测模型基于源字和源字的上下文来确定目标字是源字的正确翻译的概率。基于由生育力模型计算的概率和由感知模型计算的概率，可操作地耦合到生育力和感知模型的解码器，用于生成用于翻译源词的目标词列表。

2. 发明授权

US5467425A Building scalable N-gram language models using maximum likelihood maximum entropy N-gram models 失效
标题翻译：使用最大似然最大熵N-gram模型构建可扩展的N-gram语言模型
公开(公告)号：US5467425A
公开(公告)日：1995-11-14
申请号：US23543
申请日：1993-02-26
申请人： Raymond Lau , Ronald Rosenfeld , Salim Roukos
发明人： Raymond Lau , Ronald Rosenfeld , Salim Roukos
IPC分类号： G10L15/06 , G06F17/28 , G10L15/10 , G10L15/18 , G10L15/28 , G10L9/00
CPC分类号： G10L15/197 , G10L15/183
摘要： The present invention is an n-gram language modeler which significantly reduces the memory storage requirement and convergence time for language modelling systems and methods. The present invention aligns each n-gram with one of "n" number of non-intersecting classes. A count is determined for each n-gram representing the number of times each n-gram occurred in the training data. The n-grams are separated into classes and complement counts are determined. Using these counts and complement counts factors are determined, one factor for each class, using an iterative scaling algorithm. The language model probability, i.e., the probability that a word occurs given the occurrence of the previous two words, is determined using these factors.
摘要翻译：本发明是一种n-gram语言建模器，其显着地减少了语言建模系统和方法的存储器存储需求和收敛时间。本发明使每个n-gram与“n”个不相交类别之一对齐。对于表示训练数据中每个n-gram发生的次数的每个n-gram，确定计数。将n克分成各类，并确定补体计数。使用这些计数和补数计数因子，使用迭代缩放算法确定每个类的一个因素。使用这些因素来确定语言模型概率，即，假定出现前两个单词的单词出现的概率。

3. 发明申请

US20050237227A1 Mention-synchronous entity tracking system and method for chaining mentions 有权
标题翻译：提及同步实体跟踪系统和链接提示方法
公开(公告)号：US20050237227A1
公开(公告)日：2005-10-27
申请号：US10833256
申请日：2004-04-27
申请人： Abraham Ittycheriah , Hongyan Jing , Nandakishore Kambhatla , Xiaoqiang Luo , Salim Roukos
发明人： Abraham Ittycheriah , Hongyan Jing , Nandakishore Kambhatla , Xiaoqiang Luo , Salim Roukos
IPC分类号： G10L15/18 , H03M1/22
CPC分类号： G10L15/1822 , Y10S707/99943
摘要： A Bell Tree data structure is provided to model the process of chaining the mentions, from one or more documents, into entities, tracking the entire process; where the data structure is used in an entity tracking process that produces multiple results ranked by a product of probability scores.
摘要翻译：提供了一个贝尔数据结构来模拟从一个或多个文档到实体链接提到的过程，跟踪整个过程; 其中数据结构用于产生由概率分数的乘积排列的多个结果的实体跟踪过程。

4. 发明授权

US06246981B1 Natural language task-oriented dialog manager and method 有权
标题翻译：自然语言面向任务的对话管理和方法
公开(公告)号：US06246981B1
公开(公告)日：2001-06-12
申请号：US09200098
申请日：1998-11-25
申请人： Kishore A. Papineni , Salim Roukos , Robert T. Ward
发明人： Kishore A. Papineni , Salim Roukos , Robert T. Ward
IPC分类号： G10L1526
CPC分类号： G10L15/22 , G10L2015/228
摘要： A system for conversant interaction includes a recognizer for receiving and processing input information and outputting a recognized representation of the input information. A dialog manager is coupled to the recognizer for receiving the recognized representation of the input information, the dialog manager having task-oriented forms for associating user input information therewith, the dialog manager being capable of selecting an applicable form from the task-oriented forms responsive to the input information by scoring the forms relative to each other. A synthesizer is employed for converting a response generated by the dialog manager to output the response. A program storage device and method are also provided.
摘要翻译：用于熟悉交互的系统包括用于接收和处理输入信息并输出所识别的输入信息的表示的识别器。对话管理器被耦合到识别器，用于接收所识别的输入信息的表示，对话管理器具有用于将用户输入信息与其相关联的任务导向形式，对话管理器能够从面向任务的表单中选择适用的形式通过相对于彼此评分表格来输入信息。使用合成器来转换由对话管理器生成的响应以输出响应。还提供了一种程序存储装置和方法。

5. 发明申请

US20070061703A1 Method and apparatus for annotating a document 审中-公开
标题翻译：用于注释文档的方法和装置
公开(公告)号：US20070061703A1
公开(公告)日：2007-03-15
申请号：US11224171
申请日：2005-09-12
申请人： Nandakishore Kambhatla , Salim Roukos
发明人： Nandakishore Kambhatla , Salim Roukos
IPC分类号： G06F17/00
CPC分类号： G06F17/218 , G06F17/2247 , G06F17/241 , G06F17/278
摘要： Methods and apparatus are provided for annotating documents with one or more of entities, events and relations. Documents are annotated by presenting the document to a user; presenting the user with a list of possible entity types, wherein the list of possible entity types is configurable; and obtaining at least one mention annotation that associates a selected phrase in the document with one of the possible entity types. The selected phrase can be presented to the user, for example, based on one or more presentation rules associated with the associated entity type. The method can be implemented, for example, in a client-server configuration where a browser communicates with a remote server. A document can also be annotated by presenting the document to a user; presenting the user with a list of possible relation types, wherein the list of possible relation types is configurable; receiving at least two mention annotations from the user that each associate a selected phrase in the document with a entity type; and obtaining a relation annotation, wherein the relation annotation specifies a relation type between the at least two mention annotations.
摘要翻译：提供了用于用一个或多个实体，事件和关系来注释文档的方法和装置。通过向用户呈现文档来注释文档; 向用户呈现可能的实体类型的列表，其中可能的实体类型的列表是可配置的; 以及获得将文档中的所选短语与可能的实体类型之一相关联的至少一个提及注释。所选择的短语可以例如基于与关联的实体类型相关联的一个或多个呈现规则来呈现给用户。该方法可以例如在浏览器与远程服务器通信的客户端 - 服务器配置中实现。还可以通过向用户呈现文档来注释文档; 向用户呈现可能的关系类型的列表，其中可能的关系类型的列表是可配置的; 从所述用户接收至少两个提及注释，每个所述注释与所述文档中的所选短语与实体类型相关联; 以及获得关系注释，其中所述关系注释指定所述至少两个提及注释之间的关系类型。

6. 发明授权

US06260014B1 Specific task composite acoustic models 有权
标题翻译：具体任务复合声学模型
公开(公告)号：US06260014B1
公开(公告)日：2001-07-10
申请号：US09153222
申请日：1998-09-14
申请人： Lalit Rai Bahl , David Lubensky , Mukund Padmanabhan , Salim Roukos
发明人： Lalit Rai Bahl , David Lubensky , Mukund Padmanabhan , Salim Roukos
IPC分类号： G10L1504
CPC分类号： G10L15/26 , G10L15/22 , G10L2015/223 , G10L2015/228
摘要： A method for recognizing speech includes the steps of providing a generic model having a baseform representation of a vocabulary of words, identifying a subset of words relating to an application, constructing a task specific model for the subset of words, constructing a composite model by combining the generic and task specific models and modifying the baseform representation of the subset of words such that the subset of words are recognized by the task specific model. A system for recognizing speech includes a composite model having a generic model having a generic baseform representation of a vocabulary of words and a task specific model for recognizing a subset of words relating to an application wherein the subset of words are recognized using a modified baseform representation. A recognizer compares words input thereto with the generic model for words other than the subset of words and with the task specific model for the subset of words.
摘要翻译：一种用于识别语音的方法包括以下步骤：提供具有词汇词典的基本形式表示的通用模型，识别与应用有关的单词的子集，为所述单词子集构建任务特定模型，通过组合来构建复合模型通用和任务特定模型，并修改单词子集的基本形式表示，使得单词的子集由任务特定模型识别。用于识别语音的系统包括具有通用模型的复合模型，所述通用模型具有词汇词典的通用基本形式表示，以及用于识别与应用有关的词组的任务特定模型，其中使用经修改的基本形式表示来识别单词的子集。识别器将输入的词与除单词子集之外的单词的通用模型和词语子集的任务特定模型进行比较。

7. 发明授权

US06219638B1 Telephone messaging and editing system 有权
标题翻译：电话信息和编辑系统
公开(公告)号：US06219638B1
公开(公告)日：2001-04-17
申请号：US09185332
申请日：1998-11-03
申请人： Mukund Padmanabhan , Michael Picheny , David Nahamoo , Salim Roukos
发明人： Mukund Padmanabhan , Michael Picheny , David Nahamoo , Salim Roukos
IPC分类号： G10L1508
CPC分类号： H04M3/53366 , G10L15/22 , G10L2015/221 , H04M3/5307 , H04M2201/40 , H04M2201/60
摘要： A messaging system for receiving speech over a telephone and converting the speech to text includes a first server for receiving speech input by a user, a speech recognition system for converting the speech to text, a speech synthesizer for converting the text to speech for playing back the synthesized speech for correction by the user and a correction mechanism for enabling the user to correct the speech such that the corrected speech is provided as text for transmittal over a communication system.
摘要翻译：一种用于通过电话接收语音并将语音转换为文本的消息系统包括用于接收用户输入的语音的第一服务器，用于将语音转换为文本的语音识别系统，用于将文本转换为语音以进行回放的语音合成器用于用户校正的合成语音和用于使用户能够校正语音的校正机制，使得校正的语音被提供为用于通过通信系统传送的文本。

8. 发明授权

US5640487A Building scalable n-gram language models using maximum likelihood maximum entropy n-gram models 失效
标题翻译：使用最大似然最大熵n-gram模型构建可扩展的n-gram语言模型
公开(公告)号：US5640487A
公开(公告)日：1997-06-17
申请号：US487299
申请日：1995-06-07
申请人： Raymond Lau , Ronald Rosenfeld , Salim Roukos
发明人： Raymond Lau , Ronald Rosenfeld , Salim Roukos
IPC分类号： G10L15/06 , G06F17/28 , G10L15/10 , G10L15/18 , G10L15/28 , G10L9/00 , G10L5/06
CPC分类号： G10L15/197 , G10L15/183
摘要： The present invention is an n-gram language modeler which significantly reduces the memory storage requirement and convergence time for language modelling systems and methods. The present invention aligns each n-gram with one of "n" number of non-intersecting classes. A count is determined for each n-gram representing the number of times each n-gram occurred in the training data. The n-grams are separated into classes and complement counts are determined. Using these counts and complement counts factors are determined, one factor for each class, using an iterative scaling algorithm. The language model probability, i.e., the probability that a word occurs given the occurrence of the previous two words, is determined using these factors.
摘要翻译：本发明是一种n-gram语言建模器，其显着地减少了语言建模系统和方法的存储器存储需求和收敛时间。本发明使每个n-gram与“n”个不相交类别之一对齐。对于表示训练数据中每个n-gram发生的次数的每个n-gram，确定计数。将n克分成各类，并确定补体计数。使用这些计数和补数计数因子，使用迭代缩放算法确定每个类的一个因素。使用这些因素来确定语言模型概率，即，假定出现前两个单词的单词出现的概率。

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