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公开(公告)号：US11056103B2
公开(公告)日：2021-07-06
申请号：US16202580
申请日：2018-11-28
Inventor： Chang Hyun Kim , Young Kil Kim
Abstract: A real-time utterance verification system according to the present invention includes a speech recognition unit configured to recognize an utterance of an utterer, a memory configured to store a program for verifying the utterance of the utterer in real time, and a processor configured to execute the program stored in the memory, wherein, upon executing the program, the processor generates and stores a list of the utterance of the utterer, performs a semantic analysis on each utterance included in the list, and generates, when the utterance is determined to be an inappropriate utterance for a listener as a result of the semantic analysis, utterance restricting information corresponding to the inappropriate utterance.
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公开(公告)号：US09037449B2
公开(公告)日：2015-05-19
申请号：US13664881
申请日：2012-10-31
Inventor： Chang Hyun Kim , Young-Ae Seo , Seong Il Yang , Jinxia Huang , Jong Hun Shin , Young Kil Kim , Sang Kyu Park
CPC classification number: G06F17/2818 , G06F17/2827
Abstract: A method for establishing paraphrasing data for a machine translation system includes selecting a paraphrasing target sentence through application of an object language model to a translated sentence that is obtained by machine-translating a source language sentence, extracting paraphrasing candidates that can be paraphrased with the paraphrasing target sentence from a source language corpus DB, performing machine translation with respect to the paraphrasing candidates, selecting a final paraphrasing candidate by applying the object language model to the result of the machine translation with respect to the paraphrasing candidates, and confirming the paraphrasing target sentence and the final paraphrasing candidate as paraphrasing lexical patterns using a bilingual corpus and storing the paraphrasing lexical patterns in a paraphrasing DB. According to the present invention, the consistent paraphrasing data can be established since the paraphrasing data is automatically established.
Abstract translation: 一种用于建立机器翻译系统的释义数据的方法包括通过将对象语言模型应用于通过机器翻译源语言句子获得的翻译句子来选择释义目标句子，提取可以用释义改写的替换候选者 来自源语言语料库DB的目标句子，对释义候选者进行机器翻译，通过将对象语言模型应用于机器翻译的结果，对于释义候选者来选择最终释义候选者，并且确认释义目标句子 和最后的释义候选人作为使用双语语料库的释义词汇模式，并将释义词汇模式存储在一个改写的DB中。 根据本发明，自动建立释义数据可以建立一致的释义数据。
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公开(公告)号：US11663479B2
公开(公告)日：2023-05-30
申请号：US15896409
申请日：2018-02-14
Inventor： Yo Han Lee , Young Kil Kim
IPC: H04N19/187 , H04N19/33 , G06N3/082 , G06N3/08 , G06F40/10 , G06F40/40 , G06F40/44 , G06N3/044 , G06N3/045
CPC classification number: G06N3/082 , G06F40/10 , G06F40/40 , G06F40/44 , G06N3/044 , G06N3/045 , G06N3/08
Abstract: Provided is a method of constructing a neural network translation model. The method includes generating a first neural network translation model learning a feature of source domain data used in an unspecific field, generating a second neural network translation model learning a feature of target domain data used in a specific field, generating a third neural network translation model learning a common feature of the source domain data and the target domain data; and generating a combiner combining translation results of the first to third neural network translation models.
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公开(公告)号：US10332033B2
公开(公告)日：2019-06-25
申请号：US15405425
申请日：2017-01-13
Inventor： Oh Woog Kwon , Young Kil Kim , Yun Keun Lee
Abstract: An incremental self-learning based dialogue apparatus for dialogue knowledge includes a dialogue processing unit configured to determine a intention of a user utterance by using a knowledge base and perform processing or a response suitable for the user intention, a dialogue establishment unit configured to automatically learn a user intention stored in a intention annotated learning corpus, store information about the learned user intention in the knowledge base, and edit and manage the knowledge base and the intention annotated learning corpus, and a self-knowledge augmentation unit configured to store a log of a dialogue performed by the dialogue processing unit, detect and classify an error in the stored dialogue log, automatically tag a user intention for the detected and classified error, and store the tagged user intention in the intention annotated learning corpus.
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Patent Agency Ranking
公开(公告)号：US20240176959A1
公开(公告)日：2024-05-30
申请号：US18200778
申请日：2023-05-23
Inventor： Jeong Heo , Young-Ae SEO , Jin SEONG , Jong Hun SHIN , Ki Young Lee , Soojong LIM , Young Kil Kim , Jihee Ryu
Abstract: Provided is a method of generating a language model using crossmodal information. The method includes: receiving language-based first modality information and non-language-based second modality information; converting the first modality information into a first byte sequence; converting the second modality information into a second byte sequence; converting the first and second byte sequences into a first embedding vector and a second embedding vector by applying an embedding technique for each modality; generating semantic association information between first and second modality information by inputting the first and second embedding vectors to a crossmodal transformer; and learning the language model by setting the generated semantic association information as training data.
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公开(公告)号：US11544479B2
公开(公告)日：2023-01-03
申请号：US16751764
申请日：2020-01-24
Inventor： Yo Han Lee , Young Kil Kim
Abstract: Provided are a method and apparatus for constructing a compact translation model that may be installed on a terminal on the basis of a pre-built reference model, in which a pre-built reference model is miniaturized through a parameter imitation learning and is efficiently compressed through a tree search structure imitation learning without degrading the translation performance. The compact translation model provides translation accuracy and speed in a terminal environment that is limited in network, memory, and computation performance.
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公开(公告)号：US10366173B2
公开(公告)日：2019-07-30
申请号：US15700537
申请日：2017-09-11
Inventor： Chang Hyun Kim , Young Kil Kim , Yun Keun Lee
IPC: G10L15/16 , G06F17/28 , G10L15/26 , G10L15/10 , G06F17/21 , G06F17/27 , G10L15/04 , G10L25/78 , G06F3/0481 , G10L15/18
Abstract: The present invention relates to a device of simultaneous interpretation based on real-time extraction of an interpretation unit, the device including a voice recognition module configured to recognize voice units as sentence units or translation units from vocalized speech that is input in real time, a real-time interpretation unit extraction module configured to form one or more of the voice units into an interpretation unit, and a real-time interpretation module configured to perform an interpretation task for each interpretation unit formed by the real-time interpretation unit extraction module.
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公开(公告)号：US20190114545A1
公开(公告)日：2019-04-18
申请号：US15896409
申请日：2018-02-14
Inventor： Yo Han Lee , Young Kil Kim
Abstract: Provided is a method of constructing a neural network translation model. The method includes generating a first neural network translation model learning a feature of source domain data used in an unspecific field, generating a second neural network translation model learning a feature of target domain data used in a specific field, generating a third neural network translation model learning a common feature of the source domain data and the target domain data; and generating a combiner combining translation results of the first to third neural network translation models.
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9.发明授权Spoken dialog system based on dual dialog management using hierarchical dialog task library 有权基于双对话管理的口语对话系统，使用分层对话任务库公开(公告)号：US09230544B2
公开(公告)日：2016-01-05
申请号：US13849853
申请日：2013-03-25
Inventor： Oh Woog Kwon , Yoon Hyung Roh , Seong Il Yang , Ki Young Lee , Sang Keun Jung , Sung Kwon Choi , Eun Jin Park , Jinxia Huang , Young Kil Kim , Chang Hyun Kim , Seung Hoon Na , Young Ae Seo , Yun Jin , Jong Hun Shin , Sang Kyu Park
CPC classification number: G10L15/22 , G06F3/167 , G10L2015/225 , H04M3/4938
Abstract: The present invention relates to a spoken dialog system and method based on dual dialog management using a hierarchical dialog task library that may increase reutilization of dialog knowledge by constructing and packaging the dialog knowledge based on a task unit having a hierarchical structure, and may construct and process the dialog knowledge using a dialog plan scheme about relationship therebetween by classifying the dialog knowledge based on a task unit to make design of a dialog service convenient, which is different from an existing spoken dialog system in which it is difficult to reuse dialog knowledge since a large amount of construction costs and time is required.
Abstract translation: 本发明涉及一种基于双对话管理的口语对话系统和方法，其中使用层次对话任务库，其可以通过基于具有层次结构的任务单元构建和打包对话知识来增加对话知识的再利用，并且可以构建和 使用关于它们之间的关系的对话计划方案处理对话知识，通过对基于任务单元的对话知识进行分类，使对话服务的设计方便，这与现有的口语对话系统不同，其中难以重用对话知识，因为 需要大量的施工成本和时间。
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