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公开(公告)号：US20110295897A1
公开(公告)日：2011-12-01
申请号：US12790996
申请日：2010-06-01
申请人： Jianfeng Gao , Christopher B. Quirk , Daniel Micol Ponce , Andreas Bode , Xu Sun
发明人： Jianfeng Gao , Christopher B. Quirk , Daniel Micol Ponce , Andreas Bode , Xu Sun
IPC分类号： G06F17/30
CPC分类号： G06F16/3322 , G06F16/951
摘要： Query-correction pairs can be extracted from search log data. Each query-correction pair can include an original query and a follow-up query, where the follow-up query meets one or more criteria for being identified as a correction of the original query, such as an indication of user input indicating the follow-up query is a correction for the original query. The query-correction pairs can be segmented to identify bi-phrases in the query-correction pairs. Probabilities of corrections between the bi-phrases can be estimated based on frequencies of matches in the query-correction pairs. Identifications of the bi-phrases and representations of the probabilities of those bi-phrases can be stored in a probabilistic model data structure.
摘要翻译： 可以从搜索日志数据中提取查询校正对。 每个查询 - 校正对可以包括原始查询和后续查询，其中后续查询符合用于被标识为原始查询的校正的一个或多个标准，诸如指示后续查询的用户输入的指示， up查询是对原始查询的更正。 可以对查询校正对进行分段以识别查询校正对中的双语短语。 可以基于查询校正对中的匹配频率来估计双词组之间的校正概率。 双语短语的识别和双语短语概率的表示可以存储在概率模型数据结构中。
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公开(公告)号：US08886516B2
公开(公告)日：2014-11-11
申请号：US13409419
申请日：2012-03-01
IPC分类号： G06F17/28
CPC分类号： G06F17/289
摘要： A method of translation includes uploading a source text portion to a back end processor. The back end processor identifies a subset of translation knowledge associated with the source text portion. The back end processor downloads the subset to a front end processor. A translation engine runs on the front end processor. The translation engine generates a translation of the source text portion as a function of the subset.
摘要翻译： 一种翻译方法包括将源文本部分上传到后端处理器。 后端处理器识别与源文本部分相关联的翻译知识的子集。 后端处理器将子集下载到前端处理器。 翻译引擎在前端处理器上运行。 翻译引擎生成作为子集的函数的源文本部分的翻译。
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公开(公告)号：US08504354B2
公开(公告)日：2013-08-06
申请号：US12131144
申请日：2008-06-02
CPC分类号： G06F17/2818 , G06F17/2827
摘要： Machine translation algorithms for translating between a first language and a second language are often trained using parallel fragments, comprising a first language corpus and a second language corpus comprising an element-for-element translation of the first language corpus. Such training may involve large training sets that may be extracted from large bodies of similar sources, such as databases of news articles written in the first and second languages describing similar events; however, extracted fragments may be comparatively “noisy,” with extra elements inserted in each corpus. Extraction techniques may be devised that can differentiate between “bilingual” elements represented in both corpora and “monolingual” elements represented in only one corpus, and for extracting cleaner parallel fragments of bilingual elements. Such techniques may involve conditional probability determinations on one corpus with respect to the other corpus, or joint probability determinations that concurrently evaluate both corpora for bilingual elements.
摘要翻译： 通常使用并行片段来训练用于在第一语言和第二语言之间进行翻译的机器翻译算法，包括第一语言语料库和包括第一语言语料库的元素元素翻译的第二语言语料库。 这种培训可能涉及可能从类似来源的大型机构中提取的大型训练集，例如描述类似事件的第一种和第二种语言的新闻文章数据库; 然而，提取的片段可能相对“嘈杂”，在每个语料库中插入额外的元素。 可以设计出可以区分在仅一个语料库中表示的语料库和“单语”元素中的“双语”元素的提取技术，以及用于提取双语元素的更清洁的平行片段。 这样的技术可以涉及一个语料库相对于另一个语料库的条件概率确定，或联合概率确定，其同时评价双语单元的语料库。
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公开(公告)号：US20090299729A1
公开(公告)日：2009-12-03
申请号：US12131144
申请日：2008-06-02
IPC分类号： G06F17/27
CPC分类号： G06F17/2818 , G06F17/2827
摘要： Machine translation algorithms for translating between a first language and a second language are often trained using parallel fragments, comprising a first language corpus and a second language corpus comprising an element-for-element translation of the first language corpus. Such training may involve large training sets that may be extracted from large bodies of similar sources, such as databases of news articles written in the first and second languages describing similar events; however, extracted fragments may be comparatively “noisy,” with extra elements inserted in each corpus. Extraction techniques may be devised that can differentiate between “bilingual” elements represented in both corpora and “monolingual” elements represented in only one corpus, and for extracting cleaner parallel fragments of bilingual elements. Such techniques may involve conditional probability determinations on one corpus with respect to the other corpus, or joint probability determinations that concurrently evaluate both corpora for bilingual elements.
摘要翻译： 通常使用并行片段来训练用于在第一语言和第二语言之间进行翻译的机器翻译算法，包括第一语言语料库和包括第一语言语料库的元素元素翻译的第二语言语料库。 这种培训可能涉及可能从类似来源的大型机构中提取的大型训练集，例如描述类似事件的第一种和第二种语言的新闻文章数据库; 然而，提取的片段可能相对“嘈杂”，在每个语料库中插入额外的元素。 可以设计出可以区分在仅一个语料库中表示的语料库和“单语”元素中的“双语”元素的提取技术，以及用于提取双语元素的更清洁的平行片段。 这样的技术可以涉及一个语料库相对于另一个语料库的条件概率确定，或联合概率确定，其同时评价双语单元的语料库。
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公开(公告)号：US07593843B2
公开(公告)日：2009-09-22
申请号：US10813208
申请日：2004-03-30
IPC分类号： G06F17/28
CPC分类号： G06F17/2818 , G06F17/2881
摘要： A method of decoding an input semantic structure to generate an output semantic structure. A set of transfer mappings are provided. A score is calculated for at least one transfer mapping in the set of transfer mappings using a statistical model. At least one transfer mapping is selected based on the score and used to construct the output semantic structure.
摘要翻译： 一种解码输入语义结构以生成输出语义结构的方法。 提供一组传输映射。 使用统计模型计算一组传输映射中的至少一个传输映射的分数。 基于分数选择至少一个传输映射，并用于构建输出语义结构。
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6.发明授权System and method for machine learning a confidence metric for machine translation 有权用于机器学习机器翻译的置信度量的系统和方法公开(公告)号：US07496496B2
公开(公告)日：2009-02-24
申请号：US11725435
申请日：2007-03-19
CPC分类号： G06F17/28
摘要： A machine translation system is trained to generate confidence scores indicative of a quality of a translation result. A source string is translated with a machine translator to generate a target string. Features indicative of translation operations performed are extracted from the machine translator. A trusted entity-assigned translation score is obtained and is indicative of a trusted entity-assigned translation quality of the translated string. A relationship between a subset of the extracted features and the trusted entity-assigned translation score is identified.
摘要翻译： 训练机器翻译系统以产生指示翻译结果的质量的置信度分数。 使用机器翻译器翻译源字符串以生成目标字符串。 从机器翻译器提取表示所执行的翻译操作的特征。 获得受信任的实体分配的翻译分数，并且指示被翻译的字符串的受信任的实体分配的翻译质量。 识别提取的特征的子集与可信实体分配的翻译分数之间的关系。
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公开(公告)号：US08209162B2
公开(公告)日：2012-06-26
申请号：US11414844
申请日：2006-05-01
CPC分类号： G06F17/289
摘要： A method of translation includes uploading a source text portion to a back end processor. The back end processor identifies a subset of translation knowledge associated with the source text portion. The back end processor downloads the subset to a front end processor. A translation engine runs on the front end processor. The translation engine generates a translation of the source text portion as a function of the subset.
摘要翻译： 一种翻译方法包括将源文本部分上传到后端处理器。 后端处理器识别与源文本部分相关联的翻译知识的子集。 后端处理器将子集下载到前端处理器。 翻译引擎在前端处理器上运行。 翻译引擎生成作为子集的函数的源文本部分的翻译。
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公开(公告)号：US07725306B2
公开(公告)日：2010-05-25
申请号：US11477978
申请日：2006-06-28
CPC分类号： G06F17/2827
摘要： A method is provided for identifying phrase alignment pairs between a source sentence and a target sentence. Boundaries for a phrase in the source sentence are identified by requiring that a source word be aligned with at least one target word in a target sentence in order to form a boundary for the source phrase. Boundaries for a phrase in the target sentence are identified based on alignments between words in the source phrase and words in the target sentence. The words in the target phrase are examined to determine if any of the words are aligned with source words outside of the source phrase. If they are not aligned with source words outside of the source phrase, the source phrase and target phrase are determined to form an alignment pair and are stored as a phrase alignment pair.
摘要翻译： 提供了一种用于识别源句和目标句之间的短语对齐对的方法。 通过要求源词与目标句中的至少一个目标词对齐以形成源短语的边界来识别源句中的短语的边界。 基于目标句子中短语的边界是基于源短语中的单词和目标句子中的单词之间的对齐来确定的。 检查目标短语中的单词以确定是否有任何单词与源短语之外的源字符对齐。 如果它们不与源短语之外的源字符对齐，则确定源短语和目标短语以形成对齐对，并将其存储为短语对齐对。
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公开(公告)号：US07412385B2
公开(公告)日：2008-08-12
申请号：US10706102
申请日：2003-11-12
CPC分类号： G06F17/289 , G06F17/274 , G06F17/2765 , G06F17/2818 , Y10S707/99931
摘要： The present invention obtains a set of text segments from a cluster of different articles written about a common event. The set of text segments is then subjected to textual alignment techniques to identify paraphrases from the text segments in the text. The invention can also be used to generate paraphrases.
摘要翻译： 本发明从关于公共事件的不同文章的集群中获得一组文本段。 然后，文本段的集合经受文本对齐技术以从文本中的文本段中识别释义。 本发明也可用于产生释义。
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公开(公告)号：US08150677B2
公开(公告)日：2012-04-03
申请号：US12146531
申请日：2008-06-26
IPC分类号： G06F17/28
CPC分类号： G06F17/2872 , G06F17/2827
摘要： Many machine translation scenarios involve the generation of a language translation rule set based on parallel training corpuses (e.g., sentences in a first language and word-for-word translations into a second language.) However, the translation of a source corpus in a source language to a target corpus in a target language involves at least two aspects: selecting elements of the target language to match the elements of the source corpus, and ordering the target elements according to the semantic organization of the source corpus and the grammatic rules of the target language. The breadth of generalization of the translation rules derived from the training may be improved, while retaining contextual information, by formulating language order templates that specify orderings of small sets of target elements according to target element types. These language order templates may be represented with varying degrees of association with the alignment rules derived from the training in order to improve the scope of target elements to which the ordering rules and alignment rules may be applied.
摘要翻译： 许多机器翻译方案涉及到基于平行训练语料库（例如，第一语言中的句子和逐字翻译成第二语言）的语言翻译规则集的生成。然而，源语料库在源中的翻译 目标语言中的目标语料库的语言至少涉及两个方面：选择目标语言的元素以匹配源语料库的元素，并根据源语料库的语义组织和语法规则对目标元素进行排序 目标语言。 可以通过根据目标元素类型制定指定小组目标元素的排序的语言顺序模板，同时保留上下文信息，从而改进从训练中导出的翻译规则的广义化。 这些语言顺序模板可以以与从训练导出的对准规则的不同程度的关联来表示，以便改进可以应用排序规则和对准规则的目标元素的范围。
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