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1. 发明授权

US11475273B1 Deep convolutional neural networks for automated scoring of constructed responses 有权
公开(公告)号：US11475273B1
公开(公告)日：2022-10-18
申请号：US16827804
申请日：2020-03-24
申请人： Educational Testing Service
发明人： Derrick Higgins , Lei Chen , Michael Heilman , Klaus Zechner , Nitin Madnani
IPC分类号： G06N3/04 , G06N3/08
摘要： Systems and methods are provided for automatically scoring a constructed response. The constructed response is processed to generate a plurality of numerical vectors that is representative of the constructed response. A model is applied to the plurality of numerical vectors. The model includes an input layer configured to receive the plurality of numerical vectors, the input layer being connected to a following layer of the model via a first plurality of connections. Each of the connections has a first weight. An intermediate layer of nodes is configured to receive inputs from an immediately-preceding layer of the model via a second plurality of connections, each of the connections having a second weight. An output layer is connected to the intermediate layer via a third plurality of connections, each of the connections having a third weight. The output layer is configured to generate a score for the constructed response.

2. 发明授权

US10559225B1 Computer-implemented systems and methods for automatically generating an assessment of oral recitations of assessment items 有权
公开(公告)号：US10559225B1
公开(公告)日：2020-02-11
申请号：US15988232
申请日：2018-05-24
申请人： Educational Testing Service
发明人： Jidong Tao , Lei Chen , Chong Min Lee
IPC分类号： G10L15/00 , G09B19/04 , G06N3/04 , G10L15/183 , G10L15/16
摘要： Provide automatic assessment of oral recitations during computer based language assessments using a trained neural network to automate the scoring and feedback processes without human transcription and scoring input by automatically generating a score of a language assessment. Providing an automatic speech recognition (“ASR”) scoring system. Training multiple scoring reference vectors associated with multiple possible scores of an assessment, and receiving an acoustic language assessment response to an assessment item. Based on the acoustic language assessment automatically generating a transcription, and generating an individual word vector from the transcription. Generating an input vector by concatenating an individual word vector with a transcription feature vector, and supplying an input vector as input to a neural network. Generating an output vector based on weights of a neural network; and generating a score by comparing an output vector with scoring vectors.

3. 发明授权

US09928754B2 Systems and methods for generating recitation items 有权
公开(公告)号：US09928754B2
公开(公告)日：2018-03-27
申请号：US14215124
申请日：2014-03-17
申请人： Educational Testing Service
发明人： Su-Youn Yoon , Lei Chen , Keelan Evanini , Klaus Zechner
IPC分类号： G09B17/00 , G09B19/04 , G06F17/27 , G10L13/08
CPC分类号： G09B19/04 , G06F17/271 , G10L13/08
摘要： Computer-implemented systems and methods are provided for automatically generating recitation items. For example, a computer performing the recitation item generation can receive one or more text sets that each includes one or more texts. The computer can determine a value for each text set using one or more metrics, such as a vocabulary difficulty metric, a syntactic complexity metric, a phoneme distribution metric, a phonetic difficulty metric, and a prosody distribution metric. Then the computer can select a final text set based on the value associated with each text set. The selected final text set can be used as the recitation items for a speaking assessment test.

4. 发明授权

US09799228B2 Systems and methods for natural language processing for speech content scoring 有权
公开(公告)号：US09799228B2
公开(公告)日：2017-10-24
申请号：US14152178
申请日：2014-01-10
申请人： Educational Testing Service
发明人： Lei Chen , Klaus Zechner , Anastassia Loukina
IPC分类号： G09B7/02 , G10L15/01 , G10L15/06
CPC分类号： G09B7/02 , G10L15/01 , G10L15/063
摘要： Computer-implemented systems and methods are provided for scoring content of a spoken response to a prompt. A scoring model is generated for a prompt, where generating the scoring model includes generating a transcript for each of a plurality of training responses to the prompt, dividing the plurality of training responses into clusters based on the transcripts of the training responses, selecting a subset of the training responses in each cluster for scoring, scoring the selected subset of training responses for each cluster, and generating content training vectors using the transcripts from the scored subset. A transcript is generated for a received spoken response to be scored, and a similarity metric is computed between the transcript of the spoken response to be scored and the content training vectors. A score is assigned to the spoken response based on the determined similarity metric.

5. 发明授权

US10937444B1 End-to-end neural network based automated speech scoring 有权
公开(公告)号：US10937444B1
公开(公告)日：2021-03-02
申请号：US16196716
申请日：2018-11-20
申请人： Educational Testing Service
发明人： David Suendermann-Oeft , Lei Chen , Jidong Tao , Shabnam Ghaffarzadegan , Yao Qian
IPC分类号： G10L25/30 , G10L15/16 , G06F17/18 , G06N3/04 , G06F40/284 , G10L25/60
摘要： A system for end-to-end automated scoring is disclosed. The system includes a word embedding layer for converting a plurality of ASR outputs into input tensors; a neural network lexical model encoder receiving the input tensors; a neural network acoustic model encoder implementing AM posterior probability, word duration, mean value of pitch and mean value of intensity based on a plurality of cues; and a linear regression module, for receiving concatenated encoded features from the neural network lexical model encoder and the neural network acoustic model encoder.

6. 发明授权

US10607188B2 Systems and methods for assessing structured interview responses 有权
公开(公告)号：US10607188B2
公开(公告)日：2020-03-31
申请号：US14667006
申请日：2015-03-24
申请人： Educational Testing Service
发明人： Patrick Charles Kyllonen , Lei Chen , Michelle Paulette Martin , Isaac Bejar , Chee Wee Leong , Joanna Gorin , David Michael Williamson
IPC分类号： G06Q10/10 , G10L15/26 , G10L25/63
摘要： Systems and methods described herein utilize supervised machine learning to generate a model for scoring interview responses. The system may access a training response, which in one embodiment is an audiovisual recording of a person responding to an interview question. The training response may have an assigned human-determined score. The system may extract at least one delivery feature and at least one content feature from the audiovisual recording of the training response, and use the extracted features and the human-determined score to train a response scoring model for scoring interview responses. The response scoring model may be configured based on the training to automatically assign scores to audiovisual recordings of interview responses. The scores for interview responses may be used by interviewers to assess candidates.

7. 发明授权

US10373047B2 Deep convolutional neural networks for automated scoring of constructed responses 有权
公开(公告)号：US10373047B2
公开(公告)日：2019-08-06
申请号：US14634203
申请日：2015-02-27
申请人： Educational Testing Service
发明人： Derrick Higgins , Lei Chen , Michael Heilman , Klaus Zechner , Nitin Madnani
IPC分类号： G06N7/02 , G06N7/04 , G06N7/06 , G06N7/08 , G06N3/04 , G06N3/08
摘要： Systems and methods are provided for automatically scoring a constructed response. The constructed response is processed to generate a plurality of numerical vectors that is representative of the constructed response. A model is applied to the plurality of numerical vectors. The model includes an input layer configured to receive the plurality of numerical vectors, the input layer being connected to a following layer of the model via a first plurality of connections. Each of the connections has a first weight. An intermediate layer of nodes is configured to receive inputs from an immediately-preceding layer of the model via a second plurality of connections, each of the connections having a second weight. An output layer is connected to the intermediate layer via a third plurality of connections, each of the connections having a third weight. The output layer is configured to generate a score for the constructed response.

8. 发明申请

US20150269529A1 Systems and Methods for Assessing Structured Interview Responses 审中-公开
标题翻译：评估结构化访谈响应的系统和方法
公开(公告)号：US20150269529A1
公开(公告)日：2015-09-24
申请号：US14667006
申请日：2015-03-24
申请人： Educational Testing Service
发明人： Patrick Charles Kyllonen , Lei Chen , Michelle Paulette Martin , Isaac Bejar , Chee Wee Leong , Joanna Gorin , David Michael Williamson
IPC分类号： G06Q10/10 , G10L15/26
CPC分类号： G06Q10/1053 , G10L15/26 , G10L25/63
摘要： Systems and methods described herein utilize supervised machine learning to generate a model for scoring interview responses. The system may access a training response, which in one embodiment is an audiovisual recording of a person responding to an interview question. The training response may have an assigned human-determined score. The system may extract at least one delivery feature and at least one content feature from the audiovisual recording of the training response, and use the extracted features and the human-determined score to train a response scoring model for scoring interview responses. The response scoring model may be configured based on the training to automatically assign scores to audiovisual recordings of interview responses. The scores for interview responses may be used by interviewers to assess candidates.
摘要翻译：本文所述的系统和方法利用监督机器学习来生成用于评分面试响应的模型。该系统可以访问训练响应，其在一个实施例中是响应面试问题的人的视听记录。训练反应可能具有指定的人为因素。系统可以从训练响应的视听记录中提取至少一个递送特征和至少一个内容特征，并且使用所提取的特征和人为评分来训练用于评分访问响应的响应评分模型。响应评分模型可以基于训练来配置，以便自动将分数分配给面试响应的视听记录。采访者可以使用面试回答的评分来评估候选人。

9. 发明申请

US20150248608A1 Deep Convolutional Neural Networks for Automated Scoring of Constructed Responses 审中-公开
标题翻译：深层卷积神经网络自动评估构建的响应
公开(公告)号：US20150248608A1
公开(公告)日：2015-09-03
申请号：US14634203
申请日：2015-02-27
申请人： Educational Testing Service
发明人： Derrick Higgins , Lei Chen , Michael Heilman , Klaus Zechner , Nitin Madnani
IPC分类号： G06N3/04 , G06N3/08
CPC分类号： G06N3/04 , G06N3/08
摘要： Systems and methods are provided for automatically scoring a constructed response. The constructed response is processed to generate a plurality of numerical vectors that is representative of the constructed response. A model is applied to the plurality of numerical vectors. The model includes an input layer configured to receive the plurality of numerical vectors, the input layer being connected to a following layer of the model via a first plurality of connections. Each of the connections has a first weight. An intermediate layer of nodes is configured to receive inputs from an immediately-preceding layer of the model via a second plurality of connections, each of the connections having a second weight. An output layer is connected to the intermediate layer via a third plurality of connections, each of the connections having a third weight. The output layer is configured to generate a score for the constructed response.
摘要翻译：提供系统和方法来自动评分构造的响应。处理构造的响应以产生代表构造的响应的多个数字向量。将模型应用于多个数字向量。该模型包括被配置为接收多个数字向量的输入层，输入层经由第一多个连接连接到模型的后续层。每个连接具有第一重量。节点的中间层被配置为经由第二多个连接从模型的紧邻之前的层接收输入，每个连接具有第二权重。输出层经由第三多个连接件连接到中间层，每个连接具有第三重量。输出层被配置为为构造的响应生成分数。

10. 发明申请

US20150120379A1 Systems and Methods for Passage Selection for Language Proficiency Testing Using Automated Authentic Listening 审中-公开
标题翻译：使用自动认证听力进行语言能力测试的通行选择系统和方法
公开(公告)号：US20150120379A1
公开(公告)日：2015-04-30
申请号：US14528921
申请日：2014-10-30
申请人： Educational Testing Service
发明人： Chong Min Lee , Su-Youn Yoon , Lei Chen
IPC分类号： G06Q30/02
CPC分类号： G06Q30/02
摘要： Test designers looking for test ideas often search online for audio/video materials. To minimize the time wasted on irrelevant/inappropriate materials, this invention describes a system, apparatus, and method of retrieving media materials for generating test items. In one example, the system may query one or more data sources based on a search criteria for retrieving media materials, and receive candidate media materials based on the query, each of which including an audio portion. The system may obtain a transcription of the audio portion of each of the candidate media materials. The system may analyze the transcription for each candidate media material to identify associated characteristics. The candidate media materials may be filtered based on the identified characteristics to derive a subset of the candidate media materials. A report may then be generated for the user identifying one or more of the candidate media materials in the subset.
摘要翻译：测试设计师寻找测试想法经常在线搜索音频/视频资料。为了最小化浪费在不相关/不合适的材料上的时间，本发明描述了一种检索用于生成测试项目的介质材料的系统，设备和方法。在一个示例中，系统可以基于用于检索媒体资料的搜索准则来查询一个或多个数据源，并且基于该查询接收候选媒体资料，每一个包括音频部分。系统可以获得每个候选媒体资料的音频部分的转录。系统可以分析每个候选媒体材料的转录以识别相关特征。可以基于所识别的特征来过滤候选媒体资料以导出候选媒体资料的子集。然后可以为用户识别子集中的一个或多个候选媒体材料生成报告。

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