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1. 发明授权

US09361908B2 Computer-implemented systems and methods for scoring concatenated speech responses 有权
标题翻译：计算机实现的系统和方法，用于评分级联的语音响应
公开(公告)号：US09361908B2
公开(公告)日：2016-06-07
申请号：US13556439
申请日：2012-07-24
申请人： Klaus Zechner , Su-Youn Yoon , Lei Chen , Shasha Xie , Xiaoming Xi , Chaitanya Ramineni
发明人： Klaus Zechner , Su-Youn Yoon , Lei Chen , Shasha Xie , Xiaoming Xi , Chaitanya Ramineni
IPC分类号： G09B19/06 , G10L25/60 , G09B19/04 , G10L15/26
CPC分类号： G10L25/60 , G09B19/04 , G09B19/06 , G10L15/26
摘要： Systems and methods are provided for scoring non-native speech. Two or more speech samples are received, where each of the samples are of speech spoken by a non-native speaker, and where each of the samples are spoken in response to distinct prompts. The two or more samples are concatenated to generate a concatenated response for the non-native speaker, where the concatenated response is based on the two or more speech samples that were elicited using the distinct prompts. A concatenated speech proficiency metric is computed based on the concatenated response, and the concatenated speech proficiency metric is provided to a scoring model, where the scoring model generates a speaking score based on the concatenated speech metric.
摘要翻译：提供系统和方法来评分非本地语音。接收两个或更多个语音样本，其中每个样本是由非母语说话者说出的语音，并且其中每个样本响应于不同的提示而被说出。两个或多个样本被连接以产生用于非母语者的连接响应，其中级联响应基于使用不同提示引出的两个或多个语音样本。基于连接的响应来计算级联语音能力度量，并且将连接的语音能力度量提供给评分模型，其中评分模型基于级联的语音度量生成口语分数。

2. 发明授权

US07778834B2 Method and system for assessing pronunciation difficulties of non-native speakers by entropy calculation 有权
标题翻译：通过熵计算评估非母语者的发音困难的方法和系统
公开(公告)号：US07778834B2
公开(公告)日：2010-08-17
申请号：US12189506
申请日：2008-08-11
申请人： Derrick Higgins , Klaus Zechner , Yoko Futagi , Rene Lawless
发明人： Derrick Higgins , Klaus Zechner , Yoko Futagi , Rene Lawless
IPC分类号： G10L11/00 , G10L17/00 , G10L15/04 , G10L15/18 , G10L13/00 , G10L13/08 , G10L21/06 , G10L21/00 , G06F17/27 , G09B19/00 , G09B19/04 , G09B7/00
CPC分类号： G09B19/06 , G10L15/19
摘要： The present disclosure presents a useful metric for assessing the relative difficulty which non-native speakers face in pronouncing a given utterance and a method and systems for using such a metric in the evaluation and assessment of the utterances of non-native speakers. In an embodiment, the metric may be based on both known sources of difficulty for language learners and a corpus-based measure of cross-language sound differences. The method may be applied to speakers who primarily speak a first language speaking utterances in any non-native second language.
摘要翻译：本公开提供了一种用于评估非母语者在发音给定语音时面临的相对困难的有用指标，以及在评估和评估非母语者话语中使用这种度量的方法和系统。在一个实施例中，度量可以基于用于语言学习者的已知的困难来源和基于语料库的跨语言音差的度量。该方法可以应用于主要以任何非本地第二语言讲第一语言说话的扬声器。

3. 发明申请

US20080249773A1 METHOD AND SYSTEM FOR THE AUTOMATIC GENERATION OF SPEECH FEATURES FOR SCORING HIGH ENTROPY SPEECH 有权
标题翻译：用于自动生成高分辨率语音的语音特征的方法和系统
公开(公告)号：US20080249773A1
公开(公告)日：2008-10-09
申请号：US12140209
申请日：2008-06-16
申请人： Isaac Bejar , Klaus Zechner
发明人： Isaac Bejar , Klaus Zechner
IPC分类号： G10L15/00
CPC分类号： G10L15/063
摘要： A method and system for automatically generating a scoring model for scoring a speech sample are disclosed. One or more training speech samples are received in response to a prompt. One or more speech features are determined for each of the training speech samples. A scoring model is then generated based on the speech features. At least one of the training speech samples may be a high entropy speech sample. An evaluation speech sample is received and a score is assigned to the evaluation speech sample using the scoring model. The evaluation speech sample may be a high entropy speech sample.
摘要翻译：公开了一种用于自动生成评分模型以评分语音样本的方法和系统。响应于提示接收一个或多个训练语音样本。为每个训练语音样本确定一个或多个语音特征。然后基于语音特征生成评分模型。训练语音样本中的至少一个可以是高熵语音样本。接收评估语音样本，并使用评分模型将得分分配给评估语音样本。评估语音样本可以是高熵语音样本。

4. 发明授权

US07392187B2 Method and system for the automatic generation of speech features for scoring high entropy speech 有权
标题翻译：用于自动生成语音特征的方法和系统，用于评分高熵语音
公开(公告)号：US07392187B2
公开(公告)日：2008-06-24
申请号：US10945150
申请日：2004-09-20
申请人： Isaac Bejar , Klaus Zechner
发明人： Isaac Bejar , Klaus Zechner
IPC分类号： G10L15/00
CPC分类号： G10L15/063
摘要： A method and system for automatically generating a scoring model for scoring a speech sample are disclosed. One or more training speech samples are received in response to a prompt. One or more speech features are determined for each of the training speech samples. A scoring model is then generated based on the speech features. At least one of the training speech samples may be a high entropy speech sample. An evaluation speech sample is received and a score is assigned to the evaluation speech sample using the scoring model. The evaluation speech sample may be a high entropy speech sample.
摘要翻译：公开了一种用于自动生成评分模型以评分语音样本的方法和系统。响应于提示接收一个或多个训练语音样本。为每个训练语音样本确定一个或多个语音特征。然后基于语音特征生成评分模型。训练语音样本中的至少一个可以是高熵语音样本。接收评估语音样本，并使用评分模型将得分分配给评估语音样本。评估语音样本可以是高熵语音样本。

5. 发明授权

US08990082B2 Non-scorable response filters for speech scoring systems 有权
标题翻译：用于语音评分系统的不可评估的响应过滤器
公开(公告)号：US08990082B2
公开(公告)日：2015-03-24
申请号：US13428448
申请日：2012-03-23
申请人： Su-Youn Yoon , Derrick Higgins , Klaus Zechner , Shasha Xie , Je Hun Jeon , Keelan Evanini
发明人： Su-Youn Yoon , Derrick Higgins , Klaus Zechner , Shasha Xie , Je Hun Jeon , Keelan Evanini
IPC分类号： G10L15/00 , G09B19/06 , G10L25/60 , G10L15/26 , G10L25/78 , G10L25/90
CPC分类号： G09B19/06 , G10L15/005 , G10L15/26 , G10L25/60 , G10L25/78 , G10L25/90
摘要： A method for scoring non-native speech includes receiving a speech sample spoken by a non-native speaker and performing automatic speech recognition and metric extraction on the speech sample to generate a transcript of the speech sample and a speech metric associated with the speech sample. The method further includes determining whether the speech sample is scorable or non-scorable based upon the transcript and speech metric, where the determination is based on an audio quality of the speech sample, an amount of speech of the speech sample, a degree to which the speech sample is off-topic, whether the speech sample includes speech from an incorrect language, or whether the speech sample includes plagiarized material. When the sample is determined to be non-scorable, an indication of non-scorability is associated with the speech sample. When the sample is determined to be scorable, the sample is provided to a scoring model for scoring.
摘要翻译：用于对非本机语音进行评分的方法包括接收由非本地语音讲话者所说出的语音样本，并在语音样本上执行自动语音识别和度量提取，以产生语音样本的抄本和与语音样本相关联的语音度量。该方法还包括基于抄本和语音度量确定语音样本是可划分的还是不可读的，其中确定是基于语音样本的音频质量，语音样本的语音量，语音样本是脱离主题的，语音样本是否包含来自不正确语言的语音，或者言语样本是否包括剽窃材料。当样本被确定为不可扫描时，不合格性的指示与语音样本相关联。当样品被确定为可扫描时，将样品提供给评分模型进行评分。

6. 发明申请

US20130030808A1 Computer-Implemented Systems and Methods for Scoring Concatenated Speech Responses 有权
标题翻译：计算机实现的系统和评估连贯语音响应的方法
公开(公告)号：US20130030808A1
公开(公告)日：2013-01-31
申请号：US13556439
申请日：2012-07-24
申请人： Klaus Zechner , Su-Youn Yoon , Lei Chen , Shasha Xie , Xiaoming Xi , Chaitanya Ramineni
发明人： Klaus Zechner , Su-Youn Yoon , Lei Chen , Shasha Xie , Xiaoming Xi , Chaitanya Ramineni
IPC分类号： G10L15/00
CPC分类号： G10L25/60 , G09B19/04 , G09B19/06 , G10L15/26
摘要： Systems and methods are provided for scoring non-native speech. Two or more speech samples are received, where each of the samples are of speech spoken by a non-native speaker, and where each of the samples are spoken in response to distinct prompts. The two or more samples are concatenated to generate a concatenated response for the non-native speaker, where the concatenated response is based on the two or more speech samples that were elicited using the distinct prompts. A concatenated speech proficiency metric is computed based on the concatenated response, and the concatenated speech proficiency metric is provided to a scoring model, where the scoring model generates a speaking score based on the concatenated speech metric.
摘要翻译：提供系统和方法来评分非本地语音。接收两个或更多个语音样本，其中每个样本是由非母语说话者说出的语音，并且其中每个样本响应于不同的提示而被说出。两个或多个样本被连接以产生用于非母语者的连接响应，其中级联响应基于使用不同提示引出的两个或多个语音样本。基于连接的响应来计算级联语音能力度量，并且将连接的语音能力度量提供给评分模型，其中评分模型基于级联的语音度量生成口语分数。

7. 发明授权

US08209173B2 Method and system for the automatic generation of speech features for scoring high entropy speech 有权
标题翻译：用于自动生成语音特征的方法和系统，用于评分高熵语音
公开(公告)号：US08209173B2
公开(公告)日：2012-06-26
申请号：US12140209
申请日：2008-06-16
申请人： Isaac Bejar , Klaus Zechner
发明人： Isaac Bejar , Klaus Zechner
IPC分类号： G10L15/06
CPC分类号： G10L15/063
摘要： A method and system for automatically generating a scoring model for scoring a speech sample are disclosed. One or more training speech samples are received in response to a prompt. One or more speech features are determined for each of the training speech samples. A scoring model is then generated based on the speech features. At least one of the training speech samples may be a high entropy speech sample. An evaluation speech sample is received and a score is assigned to the evaluation speech sample using the scoring model. The evaluation speech sample may be a high entropy speech sample.
摘要翻译：公开了一种用于自动生成评分模型以评分语音样本的方法和系统。响应于提示接收一个或多个训练语音样本。为每个训练语音样本确定一个或多个语音特征。然后基于语音特征生成评分模型。训练语音样本中的至少一个可以是高熵语音样本。接收评估语音样本，并使用评分模型将得分分配给评估语音样本。评估语音样本可以是高熵语音样本。

8. 发明授权

US09087519B2 Computer-implemented systems and methods for evaluating prosodic features of speech 有权
标题翻译：用于评估语音韵律特征的计算机实现的系统和方法
公开(公告)号：US09087519B2
公开(公告)日：2015-07-21
申请号：US13424643
申请日：2012-03-20
申请人： Klaus Zechner , Xiaoming Xi
发明人： Klaus Zechner , Xiaoming Xi
IPC分类号： G10L15/00 , G10L25/03 , G10L25/90 , G10L13/10
CPC分类号： G10L25/03 , G10L13/10 , G10L25/90
摘要： Systems and methods are provided for scoring speech. A speech sample is received, where the speech sample is associated with a script. The speech sample is aligned with the script. An event recognition metric of the speech sample is extracted, and locations of prosodic events are detected in the speech sample based on the event recognition metric. The locations of the detected prosodic events are compared with locations of model prosodic events, where the locations of model prosodic events identify expected locations of prosodic events of a fluent, native speaker speaking the script. A prosodic event metric is calculated based on the comparison, and the speech sample is scored using a scoring model based upon the prosodic event metric.
摘要翻译：系统和方法用于评分语音。接收到语音样本，其中语音样本与脚本相关联。语音样本与脚本对齐。提取语音样本的事件识别度量，并且基于事件识别度量在语音样本中检测韵律事件的位置。将检测到的韵律事件的位置与模型韵律事件的位置进行比较，其中模型韵律事件的位置识别讲话者的流利的母语的韵律事件的预期位置。基于比较计算韵律事件度量，并且使用基于韵律事件度量的评分模型对语音样本进行评分。

9. 发明授权

US08478597B2 Method and system for assessing pronunciation difficulties of non-native speakers 有权
标题翻译：评估非母语者发音困难的方法和系统
公开(公告)号：US08478597B2
公开(公告)日：2013-07-02
申请号：US11328651
申请日：2006-01-10
申请人： Derrick Higgins , Klaus Zechner , Yoko Futagi , Rene Lawless
发明人： Derrick Higgins , Klaus Zechner , Yoko Futagi , Rene Lawless
IPC分类号： G06F17/27 , G10L17/00 , G10L15/04 , G10L15/18 , G10L13/00 , G10L13/08 , G10L21/06 , G10L21/00
CPC分类号： G09B19/06 , G10L15/19
摘要： The present disclosure presents a useful metric for assessing the relative difficulty which non-native speakers face in pronouncing a given utterance and a method and systems for using such a metric in the evaluation and assessment of the utterances of non-native speakers. In an embodiment, the metric may be based on both known sources of difficulty for language learners and a corpus-based measure of cross-language sound differences. The method may be applied to speakers who primarily speak a first language speaking utterances in any non-native second language.
摘要翻译：本公开提供了一种用于评估非母语者在发音给定语音时面临的相对困难的有用指标，以及在评估和评估非母语者话语中使用这种度量的方法和系统。在一个实施例中，度量可以基于用于语言学习者的已知的困难来源和基于语料库的跨语言音差的度量。该方法可以应用于主要以任何非本地第二语言讲第一语言说话的扬声器。

10. 发明授权

US08392190B2 Systems and methods for assessment of non-native spontaneous speech 有权
公开(公告)号：US08392190B2
公开(公告)日：2013-03-05
申请号：US12628611
申请日：2009-12-01
申请人： Lei Chen , Klaus Zechner , Xiaoming Xi
发明人： Lei Chen , Klaus Zechner , Xiaoming Xi
IPC分类号： G10L15/00
CPC分类号： G10L17/26 , G09B7/02 , G09B19/06 , G10L15/08 , G10L15/14 , G10L15/187 , G10L15/26
摘要： Computer-implemented systems and methods are provided for assessing non-native spontaneous speech pronunciation. Speech recognition on digitized speech is performed using a non-native acoustic model trained with non-native speech to generate word hypotheses for the digitized speech. Time alignment is performed between the digitized speech and the word hypotheses using a reference acoustic model trained with native-quality speech. Statistics are calculated regarding individual words and phonemes in the word hypotheses based on the alignment. A plurality of features for use in assessing pronunciation of the speech are calculated based on the statistics, an assessment score is calculated based on one or more of the calculated features, and the assessment score is stored in a computer-readable memory.

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