Computational and Corpus Approaches to Chinese Language Learning

268 Pages·2019·12.389 MB·

by  Xiaofei Lu, Berlin Chen

Chinese Language Learning Sciences
Xiaofei Lu · Berlin Chen
Editors
Computational and
Corpus Approaches
to Chinese Language
Learning
Chinese Language Learning Sciences
Series editors
Chin-Chuan Cheng, University of Illinois, USA; Academia Sinica, Taiwan;
National Taiwan Normal University, Taiwan
Kuo-En Chang, National Taiwan Normal University, Taiwan
Executive editors
Yao-Ting Sung, National Taiwan Normal University, Taiwan
Ping Li, Pennsylvania State University, USA
This book series investigates several critical issues embedded in fundamental,
technical, and applied research in the field of Chinese as second language
(CSL) learning and teaching, including learning mechanism in the brain,
technology application for teaching, learning and assessment. The book series
discusses these issues from the perspectives of science (evidence-based approach)
and technology. The studies in the book series use the methods from the fields of
linguistics(suchascorpuslinguisticsandcomputationallinguistics),psychological
and behavioural sciences (such as experimental design and statistical analyses),
informational technology (such as information retrieval and natural language
processing) and brain sciences (such as neuroimaging and neurolinguistics). The
book series generally covers three main interdisciplinary themes: (1) fundamental
investigation ofChinese as afirst orsecond language acquisition, (2) development
in Chinese language learning technology, and (3) applied research on Chinese
language education.
More specifically, the book series involves seven research topics:
– Language transfer mechanism in Chinese as a second language
– Factors of Chinese as a second language acquisition in childhood
– Cultural influence on Chinese acquisition
– Information technology, corpus
– Teaching material design
– Teaching strategies and teacher training
– Learning models
– Assessment methods
More information about this series at http://www.springer.com/series/13176
Xiaofei Lu Berlin Chen
(cid:129)
Editors
Computational and Corpus
Approaches to Chinese
Language Learning
123
Editors
XiaofeiLu Berlin Chen
Department ofApplied Linguistics Department ofComputer Science
ThePennsylvania State University andInformation Engineering
University Park, PA,USA National Taiwan Normal University
Taipei, Taiwan
ISSN 2520-1719 ISSN 2520-1727 (electronic)
ChineseLanguageLearning Sciences
ISBN978-981-13-3569-3 ISBN978-981-13-3570-9 (eBook)
https://doi.org/10.1007/978-981-13-3570-9
LibraryofCongressControlNumber:2018964227
©SpringerNatureSingaporePteLtd.2019
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Preface
ThepastfewdecadeshavewitnessedmuchprogressintheconstructionofChinese
corporaorientedtowardsChineselanguagepedagogyaswellasthedevelopmentof
computational tools for annotating and analyzing Chinese texts and educational
natural language processing (NLP) applications for Chinese language learning and
assessment. Chinese language teachers, learners, and testers stand to benefit from
such resources, tools, and applications in numerous productive ways. This volume
bringstogethersomeofthemostrecenttheoretical,empirical,methodological,and
technological developments in applying computational and corpus approaches to
teaching,learning,andassessingChineseasasecondorforeignlanguage.Itisour
hopethattheinsightsfromthesedevelopmentswillhelpadvancethestateoftheart
in theorizing, designing, and implementing research and practice in corpus-
informed and NLP-enabled Chinese language teaching, learning, and assessment.
Weoweaspecialthankstotheco-editorsoftheSpringerbookseriesonChinese
Language Learning Sciences, Prof. Yao-Ting Sung and Prof. Ping Li, for their
inspiring trust, support, and guidance from the very beginning of this process
through the end. Thanks also go to many colleagues and friends who have helped
shapethedirectionofthebookinvariousways,directlyorindirectly.Tonamejust
a few: Marjorie Chan, Howard Ho-Jan Chen, Hsiao-Tsung Hung, Tan Jin,
Zhuo Jing-Schmidt, Detmar Meurers, Hongyin Tao, Ming-Han Yang, and many
others.
Lastbutnotleast,wewouldliketosincerelythankLawrenceLiuandLayPeng
Ang at Springer for their impressively professional and efficient support and the
anonymous reviewers of the book proposal and manuscript for their highly
insightful and constructive comments.
University Park, USA Xiaofei Lu
Taipei, Taiwan Berlin Chen
v
Contents
Part I Introduction
Computational and Corpus Approaches to Chinese Language
Learning: An Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Xiaofei Lu and Berlin Chen
Corpus and Computational Methods for Usage-Based Chinese
Language Learning: Toward a Professional Multilingualism . . . . . . . . . 13
Zhuo Jing-Schmidt
The Corpus Approach to the Teaching and Learning of Chinese
as an L1 and an L2 in Retrospect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Jiajin Xu
Part II Tools, Resources and General Applications
Academic Chinese: From Corpora to Language Teaching. . . . . . . . . . . 57
Howard Ho-Jan Chen and Hongyin Tao
Pedagogical Applications of Chinese Parallel Corpora. . . . . . . . . . . . . . 81
Brody Bluemel
Data-Driven Adapting for Fine-Tuning Chinese Teaching Materials:
Using Corpora as Benchmarks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Wei Bo, Jing Chen, Kai Guo and Tan Jin
Part III Specific Applications
Context Analysis for Computer-Assisted Near-Synonym Learning. . . . . 121
Liang-Chih Yu, Wei-Nan Chien and Kai-Hsiang Hsu
Visualizing Stylistic Differences in Chinese Synonyms . . . . . . . . . . . . . . 145
Zheng-Sheng Zhang
vii
viii Contents
Using Corpus-Based Analysis of Neologisms on China’s New Media
for Teaching Chinese as a Second or Foreign Language . . . . . . . . . . . . 173
Wengao Gong and Huaqing Hong
Part IV Learner Language Analysis and Assessment
Acquisition of the Chinese Particle le by L2 Learners:
A Corpus-Based Approach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
Hai Xu, Xiaofei Lu and Vaclav Brezina
Mandarin Chinese Mispronunciation Detection and Diagnosis
Leveraging Deep Neural Network Based Acoustic Modeling and
Training Techniques. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
Berlin Chen and Yao-Chi Hsu
Resources and Evaluations of Automated Chinese Error Diagnosis
for Language Learners. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235
Lung-Hao Lee, Yuen-Hsien Tseng and Li-Ping Chang
Automated Chinese Essay Scoring Based on Multilevel Linguistic
Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
Tao-Hsing Chang and Yao-Ting Sung
Part I
Introduction
Computational and Corpus Approaches
to Chinese Language Learning:
An Introduction
XiaofeiLuandBerlinChen
Abstract Inthisintroductorychapter,wefirstprovideadiscussionoftherationale
andobjectivesofthebook.Wethenofferabriefreviewofthebodyofcorpuslin-
guistics research that intersects with Chinese language pedagogy and acquisition.
Thisisfollowedbyanoverviewofthestateoftheartofresearchincomputational
linguisticsandnaturallanguageprocessingthatpertainstoChineselanguageteach-
ing,learning,andassessment.Weconcludewithadescriptionoftheorganizationof
thebook.
1 RationaleandObjectivesoftheBook
The past a few decades have witnessed remarkable progress in the construction
of large corpora of spoken and written language produced by both first language
(L1) and second language (L2) speakers and writers. In addition to their proven
value in a vast range of linguistic research (McEnery and Hardie 2011), language
corporahaveincreasinglybeenusedtoinformsecondandforeignlanguageteaching,
learning,andassessment(Aijmer2009).Theplethoraoflanguagecorporahavealso
facilitatedthedevelopmentofnaturallanguageprocessing(NLP)technologieswith
various language understanding and production capabilities (Jurafsky and Martin
2008).TwotypesofNLPtechnologiesthatareespeciallyusefulinsecondandforeign
languagepedagogyandresearcharecomputationaltoolsdesignedtoautomatecorpus
annotationandanalysisatspecificlinguisticlevels(Lu2014)andeducationalNLP
applicationsdesignedtofacilitatedifferentaspectsoflanguageteachingandlearning
ortoassistwiththeassessmentofdifferentaspectsoflanguageproduction(Lu2018).
B
X.Lu( )
ThePennsylvaniaStateUniversity,UniversityPark,USA
e-mail:[e-mail]
B.Chen
NationalTaiwanNormalUniversity,Taipei,Taiwan
e-mail:[e-mail]
©SpringerNatureSingaporePteLtd.2019 3
X.LuandB.Chen(eds.),ComputationalandCorpusApproachestoChinese
LanguageLearning,ChineseLanguageLearningSciences,
https://doi.org/10.1007/978-981-13-3570-9_1