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    • 1. 发明公开
    • 외국어 끊어 읽기 제공 시스템 및 이를 이용한 외국어 문장 끊어 읽기 제공 방법
    • 用于外国语言和PHRASE BREAK提供方法的PHRASE BREAK提供商系统
    • KR1020150146233A
    • 2015-12-31
    • KR1020140076511
    • 2014-06-23
    • 포항공과대학교 산학협력단
    • 이근배방지수이종훈강세천서홍석
    • G09B5/06G09B19/06
    • G09B5/06G09B5/00G09B19/06
    • 실시예에따른외국어끊어읽기제공시스템은, 끊어읽는부분이표시된텍스트및 음성이포함된훈련용말뭉치를이용하여예측모델을훈련하는예측모델훈련부; 상기훈련된예측모델과텍스트와음성이포함된사용자발화를이용하여끊어읽을곳이예측된예측결과를생성하고, 예측결과확률을계산하는예측부; 상기훈련용말뭉치를이용하여검출모델을훈련하는검출모델훈련부; 상기훈련된검출모델과상기사용자발화를이용하여끊어읽을곳이검출된검출결과를생성하고, 검출결과확률을계산하는검출부; 및상기예측결과와상기검출결과를비교하고, 상기예측결과확률과상기검출결과확률을이용하여끊어읽기결과를표시하는피드백부를포함한다.
    • 本发明涉及一种用于以块的形式读取外语的提供系统,以及一种用于使用该语言块读取以外语写成的句子的提供方法。 根据本发明的实施例,本发明的提供系统包括:预测模型训练部分,通过使用训练语料库训练预测模型,所述训练语料库包括语音和标记有暂停的符号; 预测部分,通过使用经训练的预测模型和由文本和语音组成的用户发音来创建在哪里暂停的预测结果,并且对预测结果计算概率; 检测模型训练部分通过使用训练语料库对检测到的模型进行训练; 检测部,通过使用训练检测模型和用户发音来创建在哪里暂停的检测结果,并且计算检测结果的概率; 以及反馈部分,比较预测结果和检测结果,并通过使用预测结果和检测结果的概率来标记用于在块中读取的结果。
    • 2. 发明授权
    • 문법 오류 정정 시스템 및 이를 이용한 문법 오류 정정 방법
    • 用于精确误差校正的装置和使用其进行误差校正的方法
    • KR101374900B1
    • 2014-03-13
    • KR1020120145721
    • 2012-12-13
    • 포항공과대학교 산학협력단
    • 이근배이종훈서홍석강세천방지수이규송
    • G06F17/20G06F17/30G06F17/40G09B7/00
    • G06F17/274G06N5/04G06N99/005
    • The present invention relates to a system for correcting grammatical errors and a method for correcting grammatical errors using the same. More particularly, the system for correcting grammatical errors comprises: a learning unit for acquiring a plurality of contextual qualities according to language characteristics from a plurality of corpuses and generating a first learning classification model and a second learning classification model which are standards for diagnosing grammatical errors from the contextual qualities; and an execution unit for predicting grammatical errors for a corpus inputted by a learner using the first learning classification model, predicting grammatical errors using a first prediction result of the grammatical errors and the second learning classification model, and correcting the grammatical errors, wherein the second learning classification model is generated by a repeated learning technique using the contextual qualities extracted from the corpuses, based on the first prediction result. [Reference numerals] (10) Learning unit; (101) Contextual quality extraction unit; (102) Basic classification learning unit; (103) Basic classification model; (104) Basic classification prediction unit; (105) Meta classification learning unit; (106) Meta classification model; (107) Meta classification prediction unit; (20) Modeling unit; (30) Performing unit; (AA,BB) Training corpus; (CC) Learner sentence(input); (DD) System correction(output)
    • 本发明涉及一种用于校正语法错误的系统和一种用于使用其校正语法错误的方法。 更具体地,用于校正语法错误的系统包括:学习单元,用于根据来自多个语料库的语言特征获取多个语境质量,并且生成用于诊断语法错误的标准的第一学习分类模型和第二学习分类模型 从上下文的品质; 以及执行单元,用于使用所述第一学习分类模型预测由学习者输入的语料库的语法错误,使用所述语法错误的第一预测结果和所述第二学习分类模型来预测语法错误,以及校正所述语法错误,其中所述第二学习分类模型 基于第一预测结果,通过使用从语料库提取的语境质量的反复学习技术生成学习分类模型。 (附图标记)(10)学习单元; (101)上下文质量提取单元; (102)基础分类学习单元; (103)基本分类模型; (104)基本分类预测单元; (105)元分类学习单元; (106)元分类模型; (107)元分类预测单元; (20)建模单位; (30)执行单位; (AA,BB)训练语料库; (CC)学习者句(输入); (DD)系统校正(输出)
    • 4. 发明公开
    • 끊어읽기 훈련용 말뭉치 생성 장치 및 방법
    • 用于培养初步预测的装置和方法
    • KR1020130013128A
    • 2013-02-06
    • KR1020110074552
    • 2011-07-27
    • 포항공과대학교 산학협력단
    • 이근배이진식이종훈서홍석
    • G09B17/02G09B5/02G09B19/04G10L13/08
    • G09B17/02G09B5/02G09B19/04G10L13/086
    • PURPOSE: A corpus generator for practicing phrase break prediction, and a method thereof are provided to minimize the reflection of each transcriber`s characteristic, thereby maximizing the reflection of the general transcribers` characteristics of the predicted phrase break. CONSTITUTION: A corpus generator(100) for practicing phrase break prediction comprises: A boundary extractor(110), a boundary determiner(120), and a phrase break prediction corpus generator(130). The boundary extractor receives multiple transcription data transcribed after phrase boundaries about the same text from each of the multiple labeled transcribers and extracts phrase boundaries from each of the multiple transcription data. The boundary determiner compares each of the extracted phrase boundaries, and determines phrase boundaries satisfied with a fixed setting to a phrase break prediction. The phrase break prediction corpus generator labels the determined phrase break prediction, and generates the phrase break prediction corpus. [Reference numerals] (1000) Phrase break prediction corpus DB; (110) Boundary extractor; (120) Boundary determiner; (121) First determination module; (122) Second determination module; (130) Phrase break prediction corpus generator; (AA) Transfer data
    • 目的:提供一种用于练习短语中断预测的语料库生成器及其方法,以最小化每个转录器特征的反射,从而最大化预测短语中断的一般誊写者特征的反映。 构成:用于实施短语中断预测的语料库生成器(100)包括:边界提取器(110),边界确定器(120)和短语中断预测语料库生成器(130)。 边界提取器从多个标记的转录器中的每一个接收关于相同文本的短语边界之后转录的多个转录数据,并从多个转录数据中的每一个提取短语边界。 边界确定器比较每个提取的短语边界,并将满足固定设置的短语边界确定为短语中断预测。 短语break预测语料库生成器标记确定的短语中断预测,并生成短语break预测语料库。 [参考数字](1000)短语突破预测语料库DB; (110)边界提取器; (120)边界确定因子 (121)第一确定模块; (122)第二确定模块; (130)短语预测语料库发生器; (AA)传输数据
    • 8. 发明公开
    • 어학 학습 장치 및 어학 학습 방법
    • 用于语言学习的方法及其方法
    • KR1020130043817A
    • 2013-05-02
    • KR1020110107940
    • 2011-10-21
    • 포항공과대학교 산학협력단
    • 이근배이종훈이진식서홍석
    • G09B7/04G09B5/04G09B19/06
    • G09B7/04G09B5/04G09B19/06
    • PURPOSE: An apparatus for learning language and a method thereof are provided to offer feedback for voice input to a user by analyzing the voice input. CONSTITUTION: A first voice recognition part(110) generates a first transcribed material transcribing voice input by recognizing the voice input in a word unit. A second voice recognition part(120) generates a second transcribed material transcribing the voice input by recognizing the voice input in a phoneme unit. A standard pronunciation generation part(130) generates a third transcribed material by converting the first transcribed material into predefined standard pronunciation. An error detection part(140) generates error information for the part of the second transcribed material not satisfying a predetermined reference by comparing the second transcribed material with the third transcribed material. A feedback generation part(150) generates feedback information corresponding to the error information. [Reference numerals] (1000) Pronunciation data DB; (110) First voice recognition part; (120) Second voice recognition part; (130) Standard pronunciation generation part; (140) Error detection part; (150) Feedback generation part; (160) Expansion pronunciation generation part; (2000) Pronunciation dictionary DB; (3000) Feedback DB; (AA) Voice input
    • 目的:提供一种用于学习语言的装置及其方法,以通过分析语音输入来提供对用户的语音输入的反馈。 构成:第一语音识别部分(110)通过识别单词中的语音输入来生成转录语音输入的第一转录素材。 第二语音识别部件(120)通过识别音素单元中的语音输入来生成转录语音输入的第二转录材料。 标准发音生成部件(130)通过将第一转录材料转换为预定义的标准发音来生成第三转录材料。 错误检测部件(140)通过将第二转录材料与第三转录材料进行比较来生成不满足预定参考的第二转录材料的部分的误差信息。 反馈生成部(150)生成与错误信息对应的反馈信息。 (附图标记)(1000)发音数据DB; (110)第一语音识别部分; (120)第二语音识别部分; (130)标准发音生成部分; (140)错误检测部分; (150)反馈生成部分; (160)扩音发音部分; (2000)发音词典DB; (3000)反馈DB; (AA)语音输入
    • 10. 发明授权
    • 외국어 학습을 위한 강세 학습 시스템 및 방법
    • 应力研究系统和研究外来语言的方法
    • KR101188982B1
    • 2012-10-08
    • KR1020110072171
    • 2011-07-20
    • 포항공과대학교 산학협력단
    • 이근배이진식이종훈서홍석
    • G09B19/06G09B5/02G09B7/02G06Q50/20G10L15/00G10L15/26
    • G09B19/06G06Q50/20G09B5/02G09B7/02G10L15/005G10L15/26
    • PURPOSE: A stress learning system and method for foreign language learning are provided to effectively perform the foreign language learning. CONSTITUTION: A stress learning system for foreign language learning(100) comprises a stress estimating part(120), a stress detecting part(140), and a stress feedback part(150). The stress estimating part extracts a first feature for estimating stress in a text which is provided. The stress estimating part obtains first information corresponding to the first feature from a first database. The stress detecting part estimates stress from the text based on the first information and creates first stress. The stress detecting part receives the first feature and extracts a second feature for detecting stress in voice of a user. The stress detecting part obtains second information corresponding to the first feature and the second feature from a second database and creates second stress by detecting the stress from the voice based on the second information. The stress feedback part obtains the difference of the first stress and the second stress and provides information corresponding to the difference. [Reference numerals] (1000) Text stress corpus DB; (110) Stress estimating training part; (111) Language analyzing module; (112) Stress estimating training module; (120) Stress estimating part; (121) Language analyzing module; (122) Stress estimating module; (130) Stress detection training part; (131) Language analyzing module; (132) Voice analyzing module; (133) Stress detection training module; (140) Stress detection part; (141) Voice analyzing module; (142) Stress detection module; (150) Stress feedback part; (151) Stress comparing module; (152) Stress feedback module; (2000) Stress estimating model DB(First DB); (3000) Voice stress corpus DB; (4000) Stress detection model DB(Second DB); (AA) Text input; (BB) Voice input
    • 目的:提供外语学习的压力学习系统和方法,有效地进行外语学习。 构成:用于外语学习的应力学习系统(100)包括应力估计部分(120),应力检测部分(140)和应力反馈部分(150)。 应力估计部提取用于估计提供的文本中的应力的第一特征。 应力估计部从第一数据库获得与第一特征对应的第一信息。 应力检测部件基于第一信息来估计来自文本的压力并产生第一应力。 应力检测部接收第一特征,并提取用于检测用户声音中的压力的​​第二特征。 应力检测部分从第二数据库获得与第一特征和第二特征对应的第二信息,并且通过基于第二信息检测来自语音的压力来产生第二应力。 应力反馈部分获得第一应力和第二应力的差异,并提供与差异相对应的信息。 (附图标记)(1000)文本应力语料库DB; (110)压力估计训练部分; (111)语言分析模块; (112)压力估计训练模块; (120)应力估计部分; (121)语言分析模块; (122)压力估计模块; (130)应力检测训练部分; (131)语言分析模块; (132)语音分析模块; (133)应力检测训练模块; (140)应力检测部; (141)语音分析模块; (142)应力检测模块; (150)应力反馈部分; (151)压力比较模块; (152)应力反馈模块; (2000)应力估计模型DB(First DB); (3000)语音应力语料库; (4000)应力检测模型DB(第二DB); (AA)文字输入; (BB)语音输入