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11. 发明申请

US20170239576A1 AUTOMATED PROGRAM SYNTHESIS FROM NATURAL LANGUAGE FOR DOMAIN SPECIFIC COMPUTING APPLICATIONS 审中-公开
公开(公告)号：US20170239576A1
公开(公告)日：2017-08-24
申请号：US15440490
申请日：2017-02-23
申请人： Virginia Tech Intellectual Properties, Inc.
发明人： Michael S. Hsiao
IPC分类号： A63F13/63 , A63F13/42 , A63F13/20 , G06F17/27 , G06F3/0481
CPC分类号： A63F13/63 , A63F13/215 , A63F13/42 , G06F8/41 , G06F17/2735 , G06F17/277 , G06F17/2775 , G06F17/2785 , G06F17/2795 , G06F17/2872
摘要： Disclosed are various embodiments for automated program synthesis from a natural language for domain specific computing applications. In one embodiment, a natural language processor may be configured to parse words from a sentence of text formed in a natural language, such as English, following a grammatical structure for the natural language. The words may be compared to a dictionary to identify a token. The text formed in the natural language may be converted to an intermediate format of programming code in a programming language, such as C, where the intermediate format includes the token. The token may invoke a function or a routine of a library written in the programming language. The intermediate format may be compiled into executable program code to generate an application, such as a video game, for execution.

12. 发明申请

US20170083200A1 GENERATING A CONTEXT FOR TRANSLATING STRINGS BASED ON ASSOCIATED APPLICATION SOURCE CODE AND MARKUP 有权
公开(公告)号：US20170083200A1
公开(公告)日：2017-03-23
申请号：US15376822
申请日：2016-12-13
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION
发明人： Timothy S. Bartley , Gavin G. Bray , Elizabeth M. Hughes , Kalvinder P. Singh
IPC分类号： G06F3/0484 , G06F9/44 , G06F17/28
CPC分类号： G06F3/0484 , G06F8/40 , G06F9/454 , G06F17/2247 , G06F17/2836 , G06F17/2872
摘要： An approach to generating a context for translating strings for a graphical user interface. The approach includes a computer receiving a string to be translated and associated source code, the string identified by a unique key within the associated source code and the associated source code is markup language. The computer identifies a first logical section of the associated source code corresponding to a unique key of the string and one or more graphical user interface components within the identified logical section of the associated source code. The computer then creates a mockup image presenting the one or more graphical user interface components and the string. The computer then labels, in the created mockup image, each of the one or more graphical user interface components and the first string of the plurality of strings, and identifies one or more additional graphical user interface components.

13. 发明申请

US20170060854A1 STATISTICS-BASED MACHINE TRANSLATION METHOD, APPARATUS AND ELECTRONIC DEVICE 审中-公开
标题翻译：基于统计的机器翻译方法，装置和电子设备
公开(公告)号：US20170060854A1
公开(公告)日：2017-03-02
申请号：US15247490
申请日：2016-08-25
申请人： Alibaba Group Holding Limited
发明人： Xiaodong Zeng , Weihua Luo , Feng Lin
IPC分类号： G06F17/28 , G06F17/27
CPC分类号： G06F17/2818 , G06F17/2705 , G06F17/2785 , G06F17/2872
摘要： A statistics-based machine translation method is disclosed. The method generates probabilities of translation from a sentence to be translated to candidate translated texts based on features of the candidate translated texts that affect the probabilities of translation and a pre-generated translation probability prediction model. The features that affect probabilities of translation include at least degrees of semantic similarity between the sentence to be translated and the candidate translated texts. A preset number of candidate translated texts with highly ranked probabilities of translation are selected to serve as translated texts of the sentence to be translated. The method is able to go deep into a semantic level of a natural language when a machine translation model is constructed to avoid a semantic deviation of a translated text from an original text, thereby achieving the effect of improving the quality of translation.
摘要翻译：公开了一种基于统计的机器翻译方法。该方法基于影响翻译概率的候选翻译文本的特征和预先生成的翻译概率预测模型，生成从要翻译的句子到候选翻译文本的翻译概率。影响翻译概率的特征包括要翻译的句子与候选翻译文本之间的语义相似度至少为程度。选择具有高度排名的翻译概率的预设数量的候选翻译文本作为要翻译的句子的翻译文本。当构建机器翻译模型以避免翻译文本与原始文本的语义偏离，从而达到提高翻译质量的效果，该方法能够深入到自然语言的语义层面。

14. 发明授权

US09569422B1 Associating one or more terms in a message trail with a task entry 有权
标题翻译：将消息跟踪中的一个或多个术语与任务条目相关联
公开(公告)号：US09569422B1
公开(公告)日：2017-02-14
申请号：US15237152
申请日：2016-08-15
申请人： Google Inc.
发明人： Andrew Tomkins , Shanmugasundaram Ravikumar , Shalini Agarwal , Bo Pang , Mark Yinan Li
IPC分类号： G06F17/27
CPC分类号： G06F17/2765 , G06F3/04842 , G06F17/274 , G06F17/2755 , G06F17/2785 , G06F17/2872 , G06F17/289 , G06F17/3061 , G06F17/30616 , G06F17/30663 , G06Q10/107 , G06Q10/1093
摘要： Methods and apparatus related to determining an association between a message trail and a task entry of a user and associating an n-gram with the task entry, wherein the n-gram is based on one or more messages of the message trail. A similarity score between the n-gram and one or more aspects of the associated task entry may be determined. The similarity score may be utilized, for example, to determine when to associate the n-gram with the task entry and/or how to utilize the associated n-gram with the task entry.
摘要翻译：与确定消息跟踪和用户的任务条目之间的关联并将n-gram与所述任务条目相关联的方法和装置，其中所述n-gram基于所述消息跟踪的一个或多个消息。可以确定相关任务条目的n-gram和一个或多个方面之间的相似性得分。例如，相似度得分可以用于确定何时将n-gram与任务条目相关联和/或如何利用相关联的n-gram与任务条目。

15. 发明授权

US09547645B2 Machine translation apparatus, translation method, and translation system 有权
标题翻译：机器翻译设备，翻译方法和翻译系统
公开(公告)号：US09547645B2
公开(公告)日：2017-01-17
申请号：US14597308
申请日：2015-01-15
申请人： FUJITSU LIMITED
发明人： Masataka Kadotani , Tomoki Nagase
IPC分类号： G06F17/27 , G06F17/28
CPC分类号： G06F17/289 , G06F17/271 , G06F17/2785 , G06F17/2872
摘要： A machine translation apparatus configured to translate an input sentence and output a translated sentence in a target language, the machine translation apparatus includes a rule acquirer configured to acquire a difference between an input example sentence and a replaced example sentence which is obtained by replacing the input example sentence, and acquire a replacement rule based on the difference and each of meaning representations which indicate each relationship of words in the input example sentence and the replaced example sentence; and a translator configured to apply the replacement rule acquired by the rule acquirer to the input sentence and output the translated sentence based on the meaning representations and a meaning representation indicating of relationship of words in the input sentence.
摘要翻译：一种机器翻译装置，被配置为翻译输入的句子并以目标语言输出翻译的句子，所述机器翻译装置包括：规则获取器，被配置为获取输入的例句与替换的例句之间的差异，并且基于指示输入例句中的单词和替换的例句的每个关系的含义表示的差异和每个意义表示来获取替换规则; 以及翻译器，被配置为将由规则获取器获取的替换规则应用于输入句子，并且基于所述含义表示和指示所述输入句中的单词关系的含义表示来输出所述翻译句子。

16. 发明授权

US09542486B2 Techniques for real-time translation of a media feed from a speaker computing device and distribution to multiple listener computing devices in multiple different languages 有权
标题翻译：用于将媒体馈送从扬声器计算设备和分发实时转换到多种不同语言的多个收听者计算设备的技术
公开(公告)号：US09542486B2
公开(公告)日：2017-01-10
申请号：US14289928
申请日：2014-05-29
申请人： Google Inc.
发明人： Alexander Jay Cuthbert , Joshua James Estelle
IPC分类号： G06F17/28 , G06F17/30
CPC分类号： G06F17/30743 , G06F17/2827 , G06F17/2872 , G06F17/289
摘要： A computer-implemented technique can include receiving a media feed from a speaker computing device representing speech of a speaker user captured by the speaker computing device. The technique can include receiving a plurality of translation requests, each translation request being received from a listener computing device associated with a listener user and corresponding to a request to obtain a translated version of the media feed into a preferred language of the listener user. The technique can include determining the preferred language for each listener user. The technique can include obtaining a machine translated media feed for each of the translation requests, the machine translated media feed corresponding to a translation of the media feed from the source language to the preferred language of the listener user associated with the translation request. The technique can also include outputting the machine translated media feeds to the listener computing devices.
摘要翻译：计算机实现的技术可以包括从扬声器计算设备接收表示由扬声器计算设备捕获的扬声器用户的语音的媒体馈送。该技术可以包括接收多个翻译请求，每个翻译请求都是从与收听者用户相关联的收听者计算设备接收的，并且对应于获得媒体馈送到倾听者用户的首选语言的翻译版本的请求。该技术可以包括确定每个听众用户的首选语言。该技术可以包括获得用于每个翻译请求的机器翻译的媒体馈送，对应于媒体馈送从源语言到与翻译请求相关联的收听者用户的首选语言的翻译的机器翻译的媒体馈送。该技术还可以包括将机器翻译的媒体馈送输出到听众计算设备。

17. 发明授权

US09471562B2 Method and system for analyzing and translating various languages with use of semantic hierarchy 有权
标题翻译：使用语义层次分析和翻译各种语言的方法和系统
公开(公告)号：US09471562B2
公开(公告)日：2016-10-18
申请号：US13288953
申请日：2011-11-03
申请人： Konstantin Anisimovich , Vladimir Selegey , Konstantin Zuev
发明人： Konstantin Anisimovich , Vladimir Selegey , Konstantin Zuev
IPC分类号： G06F17/27 , G06F17/28
CPC分类号： G06F17/277 , G06F17/271 , G06F17/2755 , G06F17/2785 , G06F17/2872
摘要： A method and computer system for analyzing sentences of various languages and constructing a language-independent semantic structure are provided. On the basis of comprehensive knowledge about languages and semantics, exhaustive linguistic descriptions are created, and lexical, morphological, syntactic, and semantic analyses for one or more sentences of a natural or artificial language are performed. A computer system is also provided to implement, analyze and store various linguistic structures and to perform lexical, morphological, syntactic, and semantic analyses. As result, a generalized data structure, such as a semantic structure, is generated and used to describe the meaning of one or more sentences in language-independent form, applicable to automated abstracting, machine translation, control systems, Internet information retrieval, etc.
摘要翻译：提供了一种用于分析各种语言句子和构建语言无关语义结构的方法和计算机系统。在语言和语义综合知识的基础上，创造了详尽的语言描述，并对自然或人工语言的一个或多个句子进行词汇，形态，句法和语义分析。还提供了一种计算机系统来实现，分析和存储各种语言结构，并进行词法，形态，句法和语义分析。因此，生成广义数据结构，如语义结构，并用于描述语言无关形式的一个或多个句子的含义，适用于自动抽象，机器翻译，控制系统，互联网信息检索等。

18. 发明申请

US20160179792A1 Dynamic Language Translation of Web Site Content 审中-公开
标题翻译：网站内容的动态语言翻译
公开(公告)号：US20160179792A1
公开(公告)日：2016-06-23
申请号：US15058257
申请日：2016-03-02
申请人： MOTIONPOINT CORPORATION
发明人： Enrique Travieso , Eugenio Alvarez , Charles Whiteman
IPC分类号： G06F17/28 , G06F17/30 , H04L29/08
CPC分类号： G06F17/3087 , G06F17/211 , G06F17/218 , G06F17/2247 , G06F17/2288 , G06F17/275 , G06F17/2827 , G06F17/2836 , G06F17/2872 , G06F17/289 , G06F17/30554 , G06F17/30882 , G06F17/30887 , G06F17/3089 , G06F17/30893 , G06F17/30899 , G10L15/005 , H04L67/02
摘要： Methods, systems, and computer readable medium for providing translated web content with translated URLs. A request is received content in a second language translated from content in a first language. The content in the first language is obtained from the first Internet source. One or more links are identified from the content in the first language. Each original URL is divided into one or more translatable URL components in the first language. Whether the one or more translatable URL components in each original URL have been previously translated into the second language and stored as translated URL components is determined. If there is at least one translatable URL component previously translated and stored as a corresponding translated URL component, a translated URL in the second language for each original URL is generated. The content in the second language with translated URLs is created.
摘要翻译：方法，系统和计算机可读介质，用于向翻译的URL提供翻译的网页内容。以第一语言的内容翻译的第二语言的接收内容的请求。第一语言的内容是从第一个互联网来源获得的。从第一语言的内容中识别一个或多个链接。每个原始URL分为第一语言的一个或多个可翻译的URL组件。确定每个原始URL中的一个或多个可翻译URL组件是否已经被翻译成第二语言并被存储为翻译的URL组件。如果至少有一个可翻译的URL组件被翻译并存储为相应的翻译的URL组件，则生成每个原始URL的第二语言的翻译的URL。创建具有翻译URL的第二语言的内容。

19. 发明授权

US09367541B1 Terminological adaptation of statistical machine translation system through automatic generation of phrasal contexts for bilingual terms 有权
标题翻译：统计机器翻译系统的术语适应，通过自动生成双语术语的短语语境
公开(公告)号：US09367541B1
公开(公告)日：2016-06-14
申请号：US14600561
申请日：2015-01-20
申请人： Xerox Corporation
发明人： Christophe Servan , Marc Dymetman
IPC分类号： G06F17/28
CPC分类号： G06F17/2827 , G06F17/278 , G06F17/2872
摘要： A method for terminological adaptation includes receiving a vocabulary pair including source and target language terms. Each term is in a class which includes a set of sequences. Contextual phrase pairs are extracted from a bilingual training corpus, each including source and target phrases. The phrases each include a sequence of the same class as the respective source and target terms as well as some associated context. Templates are generated, based on the contextual phrase pairs. In each template the source and target sequences of a contextual phrase pair are replaced with respective placeholders, each denoting the respective class of the sequence. Candidate phrase pairs are generated from these templates. In each candidate phrase pair, the placeholders of one of the templates are replaced with respective terms of a vocabulary pair of the same class. Some candidate phrase pairs are incorporated into a phrase table of a machine translation system.
摘要翻译：用于术语适应的方法包括接收包括源和目标语言术语的词汇对。每个术语都包含一组序列。从双语训练语料库中提取语境短语对，每个语料包括源词和目标短语。每个短语包括与相应的源和目标术语以及一些相关联的上下文相同类别的序列。基于上下文短语对生成模板。在每个模板中，上下文短语对的源和目标序列被替换为相应的占位符，每个占位符表示序列的相应类。从这些模板生成候选词组。在每个候选短语对中，其中一个模板的占位符被相同类的词汇对的相应术语替换。一些候选短语对被合并到机器翻译系统的短语表中。

20. 发明申请

US20160147740A1 ADAPTING MACHINE TRANSLATION DATA USING DAMAGING CHANNEL MODEL 有权
标题翻译：使用破坏通道模型适配机器翻译数据
公开(公告)号：US20160147740A1
公开(公告)日：2016-05-26
申请号：US14552200
申请日：2014-11-24
申请人： Microsoft Technology Licensing, LLC
发明人： Qin Gao , William D. Lewis , Nicholas William Ruiz
IPC分类号： G06F17/28 , G10L15/06
CPC分类号： G06F17/289 , G06F9/454 , G06F17/2872 , G10L13/08 , G10L15/063 , G10L15/22 , G10L15/26 , G10L15/265
摘要： A speech-to-speech (S2S) translation system may utilize a damaging channel model to adapt machine translation (MT) training data so that a MT engine of the S2S translation system that is trained with the adapted training data can make better use of output received from an automated speech recognition (ASR) engine of the S2S translation system. The S2S translation system may include a MT training module that uses MT technology in order to simulate a particular ASR engine output by treating the ASR engine as a “noisy channel”. A process may include modeling ASR errors of a particular ASR engine based at least in part on output of the ASR engine to create an ASR simulation model, and performing machine translation to generate training data based at least in part on the ASR simulation model. The MT engine of the S2S translation system may then be trained using the generated training data.
摘要翻译：语音到语音（S2S）翻译系统可以利用破坏性信道模型来适应机器翻译（MT）训练数据，使得用适配的训练数据训练的S2S翻译系统的MT引擎可以更好地利用输出从S2S翻译系统的自动语音识别（ASR）引擎接收。 S2S翻译系统可以包括使用MT技术的MT训练模块，以通过将ASR引擎视为“噪声通道”来模拟特定的ASR发动机输出。过程可以包括至少部分地基于ASR引擎的输出来建模ASR仿真模型来建模特定ASR引擎的ASR错误，以及至少部分地基于ASR仿真模型执行机器翻译来生成训练数据。然后可以使用生成的训练数据训练S2S翻译系统的MT引擎。

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