-
公开(公告)号：US11475273B1
公开(公告)日：2022-10-18
申请号：US16827804
申请日：2020-03-24
Applicant: Educational Testing Service
Inventor： Derrick Higgins , Lei Chen , Michael Heilman , Klaus Zechner , Nitin Madnani
Abstract: 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.
-
公开(公告)号：US10559225B1
公开(公告)日：2020-02-11
申请号：US15988232
申请日：2018-05-24
Applicant: Educational Testing Service
Inventor： Jidong Tao , Lei Chen , Chong Min Lee
IPC: G10L15/00 , G09B19/04 , G06N3/04 , G10L15/183 , G10L15/16
Abstract: 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.
-
公开(公告)号：US09928754B2
公开(公告)日：2018-03-27
申请号：US14215124
申请日：2014-03-17
Applicant: Educational Testing Service
Inventor： Su-Youn Yoon , Lei Chen , Keelan Evanini , Klaus Zechner
CPC classification number: G09B19/04 , G06F17/271 , G10L13/08
Abstract: 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.
-
公开(公告)号：US09799228B2
公开(公告)日：2017-10-24
申请号：US14152178
申请日：2014-01-10
Applicant: Educational Testing Service
Inventor： Lei Chen , Klaus Zechner , Anastassia Loukina
CPC classification number: G09B7/02 , G10L15/01 , G10L15/063
Abstract: 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.
-
公开(公告)号：US10755595B1
公开(公告)日：2020-08-25
申请号：US15708213
申请日：2017-09-19
Applicant: Educational Testing Service
Inventor： Lei Chen , Klaus Zechner , Anastassia Loukina
Abstract: 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.
-
Patent Agency Ranking
公开(公告)号：US10706738B1
公开(公告)日：2020-07-07
申请号：US16392010
申请日：2019-04-23
Applicant: Educational Testing Service
Inventor： Lei Chen , Gary Feng , Chee Wee Leong , Christopher Kitchen , Chong Min Lee
IPC: G09B19/00
Abstract: Systems and methods are described for providing a multi-modal evaluation of a presentation. A system includes a motion capture device configured to detect motion an examinee giving a presentation and an audio recording device configured to capture audio of the examinee giving the presentation. One or more data processors are configured to extract a non-verbal feature of the presentation based on data collected by the motion capture device and an audio feature of the presentation based on data collected by the audio recording device. The one or more data processors are further configured to generate a presentation score based on the non-verbal feature and the audio feature.
-
公开(公告)号：US10176365B1
公开(公告)日：2019-01-08
申请号：US15133640
申请日：2016-04-20
Applicant: Educational Testing Service
Inventor： Vikram Ramanarayanan , Lei Chen , Chee Wee Leong , Gary Feng , David Suendermann-Oeft
Abstract: Computer-implemented systems and methods for evaluating a performance are provided. Motion of a user in a performance is detected using a motion capture device. Data collected by the motion capture device is processed with a processing system to identify occurrences of first and second types of actions by the user. The data collected by the motion capture device is processed with the processing system to determine values indicative of amounts of time between the occurrences. A non-verbal feature of the performance is determined based on the identified occurrences and the values. A score for the performance is generated using the processing system by applying a computer scoring model to the non-verbal feature.
-
公开(公告)号：US09984682B1
公开(公告)日：2018-05-29
申请号：US15474440
申请日：2017-03-30
Applicant: Educational Testing Service
Inventor： Jidong Tao , Lei Chen , Chong Min Lee
CPC classification number: G09B19/04 , G06N3/04 , G10L15/16 , G10L15/183
Abstract: 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.
-
9.发明授权Computer-implemented systems and methods for content scoring of spoken responses 有权计算机实现的语音响应内容评分系统和方法公开(公告)号：US09218339B2
公开(公告)日：2015-12-22
申请号：US13688306
申请日：2012-11-29
Applicant: Educational Testing Service
Inventor： Klaus Zechner , Keelan Evanini , Lei Chen , Shasha Xie , Wenting Xiong , Fei Huang , Jana Sukkarieh , Miao Chen
CPC classification number: G06F17/28 , G09B19/06 , G10L15/1815 , G10L2015/088
Abstract: Systems and methods are provided for scoring a non-scripted speech sample. A system includes one or more data processors and one or more computer-readable mediums. The computer-readable mediums are encoded with a non-scripted speech sample data structure, where the non-scripted speech sample data structure includes: a speech sample identifier that identifies a non-scripted speech sample, a content feature extracted from the non-scripted speech sample, and a content-based speech score for the non-scripted speech sample. The computer-readable mediums further include instructions for commanding the one or more data processors to extract the content feature from a set of words automatically recognized in the non-scripted speech sample and to score the non-scripted speech sample by providing the extracted content feature to a scoring model to generate the content-based speech score.
Abstract translation: 提供了系统和方法来评分非脚本语音样本。 系统包括一个或多个数据处理器和一个或多个计算机可读介质。 计算机可读介质用非脚本语音样本数据结构编码，其中非脚本化语音样本数据结构包括：识别非脚本化语音样本的语音样本标识符，从非脚本化语音样本数据结构提取的内容特征 语音样本和非脚本语音样本的基于内容的语音分数。 所述计算机可读介质还包括用于命令所述一个或多个数据处理器从在非脚本语音样本中自动识别的一组单词提取所述内容特征并通过提供所提取的内容特征来对所述非脚本语音样本进行评分的指令 以得分模型生成基于内容的语音分数。
-
公开(公告)号：US10937444B1
公开(公告)日：2021-03-02
申请号：US16196716
申请日：2018-11-20
Applicant: Educational Testing Service
Inventor： David Suendermann-Oeft , Lei Chen , Jidong Tao , Shabnam Ghaffarzadegan , Yao Qian
Abstract: 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.
-
-
-
-
-
-
-
-
-
Search Results
27
records
(took 0.032 seconds)
