Jian Cheng


2019

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Overcoming the bottleneck in traditional assessments of verbal memory: Modeling human ratings and classifying clinical group membership
Chelsea Chandler | Peter W. Foltz | Jian Cheng | Jared C. Bernstein | Elizabeth P. Rosenfeld | Alex S. Cohen | Terje B. Holmlund | Brita Elvevåg
Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology

Verbal memory is affected by numerous clinical conditions and most neuropsychological and clinical examinations evaluate it. However, a bottleneck exists in such endeavors because traditional methods require expert human review, and usually only a couple of test versions exist, thus limiting the frequency of administration and clinical applications. The present study overcomes this bottleneck by automating the administration, transcription, analysis and scoring of story recall. A large group of healthy participants (n = 120) and patients with mental illness (n = 105) interacted with a mobile application that administered a wide range of assessments, including verbal memory. The resulting speech generated by participants when retelling stories from the memory task was transcribed using automatic speech recognition tools, which was compared with human transcriptions (overall word error rate = 21%). An assortment of surface-level and semantic language-based features were extracted from the verbal recalls. A final set of three features were used to both predict expert human ratings with a ridge regression model (r = 0.88) and to differentiate patients from healthy individuals with an ensemble of logistic regression classifiers (accuracy = 76%). This is the first ‘outside of the laboratory’ study to showcase the viability of the complete pipeline of automated assessment of verbal memory in naturalistic settings.

2015

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Identifying Patterns For Short Answer Scoring Using Graph-based Lexico-Semantic Text Matching
Lakshmi Ramachandran | Jian Cheng | Peter Foltz
Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications

2014

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Automatic Assessment of the Speech of Young English Learners
Jian Cheng | Yuan Zhao D’Antilio | Xin Chen | Jared Bernstein
Proceedings of the Ninth Workshop on Innovative Use of NLP for Building Educational Applications

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Syllable and language model based features for detecting non-scorable tests in spoken language proficiency assessment applications
Angeliki Metallinou | Jian Cheng
Proceedings of the Ninth Workshop on Innovative Use of NLP for Building Educational Applications

2011

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Performance of Automated Scoring for Children’s Oral Reading
Ryan Downey | David Rubin | Jian Cheng | Jared Bernstein
Proceedings of the Sixth Workshop on Innovative Use of NLP for Building Educational Applications

2009

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Automated Assessment of Spoken Modern Standard Arabic
Jian Cheng | Jared Bernstein | Ulrike Pado | Masanori Suzuki
Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications