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【回看】第一届“人工智能时代的语言学研究”国际会议

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直播:10月26-27日
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人工智能时代的背景下,科技迅速发展,随之而来的是各种与语言相关的需求。语言是人类最复杂的一种智能,是关系着国家核心利益的重要因素,与经济、政治、文化发展紧密相关。业界专家指出,“在人工智能领域,懂语言者得天下”。语言学研究对于人工智能有着重要的作用,对语言有处理能力是人工智能的一种高级表现形式。如何在人工智能的时代背景下开展语言学研究,是当今语言学者们需要思考和面对的问题。为了促进人工智能时代的语言学研究,加强国内外语言学研究者之间的交流,使在语言学领域工作的学者们能够从容应对人工智能给语言学未来研究及教学带来的机遇与挑战,大连海事大学外国语学院将于2019年10月25-27日举办第一届“人工智能时代的语言学研究”国际会议。诚挚欢迎国内外各高校和研究机构从事语言学研究的学者及硕、博士生踊跃参会。

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FRIDAY 25 OCTOBER 2019

TIME

CONTENTS

VENUE

09:00-20:00

Registration

Haichuang Jianguo Hotel

18:00-19:30

Conference Dinner

1st Floor, Maritime Apartment

SATURDAY 26 OCTOBER 2019

TIME

CONTENTS

VENUE

08:30-08:45

Opening Ceremony

Professor XU Bin

105
Lecture Hall,
School of Foreign Languages (SFL)

Welcome Speech

Professor ZHAO Youtao
(Vice President of Dalian Maritime University)

 

Keynote Speech

Chair

08:45-09:25

①Professor FENG Zhiwei
Machine Translation and Artificial Intelligence

Professor ZENG Gang
(Dalian Maritime University)

09:25-10:05

②Professor Key-Sun Choi
Semantic Web and Natural Language – Learning by Reading Text

Professor GAO Wei
(Dalian University)

10:05-10:20

Group Photo

10:20-10:40

Tea Break

10:40-11:20

③Professor LIANG Maocheng
Automated Evaluation of Translation Scripts in a Large-Scale Translation Contest

Professor ZHANG Yan
(Shanghai Maritime University)

11:20-12:00

④Professor Christian Boitet
Computational Linguistics Research in the Era of Artificial Intelligence

Professor GAO Yang
(Dalian Maritime University)

12:10-13:10

Conference Luncheon

Maritime Apartment

13:30-14:10

⑤Professor FU Xingshang
Recognition of Language Resources under the Background of Intelligent Revolution

Professor WANG Xuelei
(Hangzhou Normal University)

105
Lecture Hall,
SFL

14:10-14:50

⑥Professor Wolfgang Teubert
Adverse Aspects of the Digitisation of Discourse

Professor ZHANG Li
(Shanghai Jiao Tong University)

14:50-15:30

⑦Professor CHEN Shengquan
Machine Translation and Human Translation

Professor LIU Jian
(Hengyang Normal University)

TIME

CONTENTS

VENUE

15:30-15:50

Tea Break

105 
Lecture Hall,
SFL

15:50-16:30

⑧Professor Christina Alexandris
Visualizing Pragmatic Features in Spoken Interaction: Intentions, Behavior and Evaluation Intentions, Behavior and Evaluation

Professor LIU Hui
(Heilongjiang University)

16:30-17:10

⑨Professor DENG Yaochen
Corpus Linguistics Research in the Era of Artificial Intelligence

Professor CHENG Xin
(Dalian Maritime University)

17:10-18:30

Conference Dinner

Maritime Apartment

SUNDAY 27 OCTOBER 2019

8:30-11:00

Parallel Session

Commentator/Chair

Venue

1. Research on Neural Mechanism of Language Cognition

Professor GAO Wei
(Dalian University)

301, SFL

Professor GAO Yang
(Dalian Maritime University)

2. Corpus Linguistics Research①(直播)

Professor LEI Lei
(Huazhong University of Science and Technology)

302, SFL

Professor XU Yingying
(Dalian Maritime University)

3. Corpus Linguistics Research②

Professor DENG Yaochen
(Dalian University of Foreign Languages)

303, SFL

Professor ZHAO Xiaodong
(Dalian Maritime University)

4. Translation Technology Education and Research in the Era of Artificial Intelligence

Professor CHENG Xin
(Dalian Maritime University)

304, SFL

Professor ZHANG Yan
(Shanghai Maritime University)

5. Maritime English Education and Research

Professor Se-Eun Jhang
(Korea Maritime and Ocean University)

Yuexiang Reading Room,
4th Floor

Professor SHI Chaojian
(Shanghai Maritime University)

11:00-11:30

Summary & Closing Ceremony

Professor ZENG Gang
(Dalian Maritime University)

105, SFL

11:30-13:00

Conference Luncheon

Maritime Apartment

 

Departure

按发言顺序/Arranged in speech order

FENG Zhiwei
Dr. FENG Zhiwei is a senior research fellow and professor of computational linguistics, Institute of Applied Linguistics, the Ministry of Education (PRC). Now he is council member of Association of Artificial Intelligence of China, member of Standardization Committee of State Language Commission, assessment member of China National Natural Science Foundation, assessment member of National Social Science Fund, consultant of Hong Kong Terminology Association, member of Consultant Committee of International Language Resources and Evaluation Congress (LREC), editorial board member of International Journal of Corpus Linguistics (IJCL, Amsterdam) , International Journal of Chinese and Computing (IJCC, Singapore), Chinese Language (Zhongguo Yuwei, Beijing), Chinese Science and Technology Terms Journal (Beijing), Research in Corpus and Discourse (Continuum Press, UK),. He has published 40 monograph books and more than 400 scientific papers.

Machine Translation and Artificial Intelligence

Abstract 
The paper describes the parallel development of machine translation and artificial intelligence, explains the close relationship between machine translation and artificial intelligence, analyzes principles and approaches of rule-based machine translation, statistical machine translation and neural machine translation. The paper points out that both machine translation and artificial intelligence are not ripe enough in present, they situate still in the early stage of development.

Key wordsmachine translation, artificial intelligence, rule-based machine translation, statistical machine translation, neural machine translation, deep learning

Key-Sun Choi
Dr. Key-Sun Choi is a professor of School of Computing at KAIST (Korea Advanced Institute of Science and Technology) since 1988. He received Order of Service Merit for his contribution to Korean language resource & processing and its globalization (2015). He had also received the Eugen Wüster Prize (2014). He had been the Head of Computer Science Department in KAIST (2006-2011). He has also served for ISO/TC37/SC4 (language resource management standards) as its founding secretary since 2002. He has led the group under the Semantic Web Research Center. He had founded and directed Korterm (Korea Terminology Research Center for Natural Language and Knowledge Engineering, 1998) and Bora (National Research Resource Bank for Language and Annotation, 2003). He had been an invited researcher in NEC C&C Lab of Japan (1987-1988), a visiting scholar of CSLI of Stanford University (1997), and an invited researcher of NHK Science & Technology Research Laboratories (2002). His areas of expertise are natural language processing, ontology and knowledge engineering, semantic web and linked data, and their infrastructure including text analytics. He had served the President (2009-2010) of AFNLP (Asia Federation of Natural Language Processing), and the President (2006) of Korean Cognitive Science Society.

Semantic Web and Natural Language – Learning by Reading Text

Abstract 
Machine reading is about learning knowledge by reading text and adding it to the already existing knowledge. Such learned knowledge is represented in an ontology-schematic triplet, for which the semantic web community has developed a distributed linked data web who is interpretable by machine. A triplet as a factual knowledge is to represent a relation between two entities under a given ontology schema for a unit of knowledge base. This talk is to introduce a whole process of machine reading in two facets of knowledge extraction and graph construction. knowledge extraction is a process based on natural language processing while graph construction is to handle with knowledge graph, a usual data structure of knowledge base. Such learning process could be iteratively evolved based on the growing knowledge with reducing the noise of erroneously learned knowledge unit. Issues and utilization will be proposed.

LIANG Maocheng
Dr. LIANG Maocheng is a professor of Applied Linguistics at Beihang University. Professor Liang is currently the chairperson of the Corpus Linguistics Society of China. His research interests include Corpus Linguistics, Second Language Writing, Natural Language Processing, and Data Science. In recent years, his research focuses on Deep Learning, Distributional Semantics, and Automated Writing Evaluation. He is the author of four monographs and more than 50 journal articles, and the system architect for iWrite, an online tutoring and diagnostic system for EFL writing.

Automated Evaluation of Translation Scripts in a Large-Scale Translation Contest

Abstract
Translation is a common performance task for foreign language learners. The evaluation of translation scripts, however, is not only labor-intensive and time-consuming, but also rather subjective and prone to low reliability. The study of the automated evaluation of translation is therefore of immediate practical significance.

This study draws on the state-of-the-art Doc2vec technology in NLP to construct a model for the automated evaluation of translation. The model was then used to generate a score for each of the 11,049 translation scripts collected from the Han Suyin Translation Contest. When the machine-generated scores were compared with human-generated scores, it was found that the Doc2vec-based model can produce scores with high reliability and validity. The model can efficiently identify features of good translation, and can therefore be reliably used as a second rater in large-scale translation tests.

Some of the limitations in the automated evaluation of translation are also discussed.

Key wordstranslation, automated evaluation, Doc2vec

Christian Boitet
Dr. Christian Boitet is emeritus professor at Université Grenoble Alpes (UGA) and member of the LIG lab, after having been between 1977 and 2016 full professor of computer science at Université Joseph Fourier (UJF). He has taught programming, algorithmics, compiler construction, formal languages & automata, elementary logic, formal systems, and natural language processing. He is one of the authors of Ariane-G5, GETA’s generator of MT systems.  He has presented communications in many national and international conferences, published in various journals and books, and edited a book dedicated to the presentation of Pr. Vauquois’ scientific work, as well as several international conference proceedings. He is a member of ICCL since 1988 and has been Programme co-Chair of COLING-1992 (Nantes), COLING-ACL’98 (Montréal), and COLING-2012 (Mumbai). He is and has been a regular reviewer for many journals and conferences, and has served in the programme committees of many congresses. His current interests include personal dialogue-based MT for monolingual authors (GETA’s LIDIA project, international UNL project), speech translation (aiming at the medical domain), machine helps to translators and interpreters, integration of speech processing inspired techniques in MT (hybrid approaches), multilingual lexical databases, and specialized languages and environments for lingware engineering and linguistic research (Ariane-Y project).

Computational Linguistics Research in the Era of AI

Abstract
This paper retraces the numerous interactions between Computational Linguistics (CL) and Artificial Intelligence (AI) since their earliest days, about 1950. The 1950-70 period saw the first modelling of natural languages (LN) through mathematical methods (formal ”static” grammars, dictionaries, transformational grammars) and the first Machine Translation projects, while AI centered on automatic (symbolic) theorem-proving and proposed the first Neural Net (NN), the Perceptron. A relatively large but high quality MT system had been demonstrated, PhD theses had produced the first automatic speech recognition (ASR) and synthesis (TTS) systems, and LUNAR, the first intelligent NL-based interface with a database, was operational.

The 1970-90 period saw the development of many MT operational systems (about 30 in Japan only), some with very large coverage, and a particular case, METEO, dedicated to weather bulletins, many expert systems were developed, based on knowledge bases fed by cogniticians, and CMU produced KBMT-89, the first prototype MT system using the ontology of the domain of its ”sublanguage”. During that period, empirical methods based on large sets of examples were developed, first for voice recognition, then for MT. And Harpy, based on Hidden Markov Models (HMMs) clearly beat knowledge-based systems.

The 1990-2010 period has been marked by R&D in speech translation on the CL side. International projects led by Japan (CSTAR) and Germany (VerbMobil) led to wearable systems, in particular Jibbigo (2010), working offline on mobile phones and tablets. On the written side, Example-Based MT (EBMT), an more specifically statistical MT (SMT), enjoyed an extraordinary development, leading to GoogleTranslate offering free large coverage MT between more than 100 languages. Knowledge-based systems like KANT (follower of KBMT-89) and MedSLT were mature, and AI had not only an immense success with Deep Blue beating Kasparov at chess in 1997, but also another one with Watson winning the Jeopardy! competition in 2011. Now, Information Retrieval (IR) could give way to intelligent question answering (Q/A), because structured information can be automatically extracted from NL documents without the need of cogniticians. A lesson of that period is the ”CAQ” metatheorem: for a given task like MT, or intelligent Q/A, coverage x automaticity x quality can never reach 100%. However, one can compromise on 1 factor and get the 2 others at (nearly) 100%. Another one, derived from research in EBMT, is that, in NL utterances, 96% of analogies of form are also analogies of meaning. That explains why form-based MT methods like EBMT and SMT (and later NMT) can work at all, and so well (on ”learnable” sublanguages).

We are in the middle of the 2010-2020 period. The most remarkable turn so far has been the use of very large multilayer (often convolutional) neural nets, rendered possible by the immense progress in hardware (GPUs as well as 512-core processors). But the ”human-specific” tasks of CL and AI, those (unlike face recognition or movement control) that differentiate humans from animals, are not handled in a satisfactory way, because the systems cannot explain their decisions, contrary to expert systems of the 80’s and the modern Q/A systems like Watson. Also, NN-based systems are very anti-ecological, gobbling up enormous amounts of computing power and computing space. That in turn leads to ethical problems: everything has to be processed ”on the Cloud”, and tasks or communities not having enough monetary (or linguistic) resources cannot be serviced. The final part of this paper outlines directions of research in CL that can lead to enabling multilingual access to information for speakers of the many languages that are currently under-resourced, although they are very active on the web.

FU Xingshang
Dr. FU Xingshang is a distinguished researcher and professor of the center for innovation of language resources of Beijing Language and Culture University and a former director and doctoral supervisor of the Institute of computational linguistics, Heilongjiang University. He is undertaking the research project of “Sino- Russian economic and trade cooperation database and Russian Chinese intelligent comprehensive service platform” of the center for advanced and innovative language resources. He is mainly engaged in the teaching and scientific research of computational linguistics, semantics and other disciplines, as well as the research and development of natural language automatic processing system. He has presided over and undertaken 4 major and general projects of the Ministry of Education and National Humanities and Social Sciences, 4 provincial projects, 5 monographs and more than 30 papers. He is the first to push the palm computer system of the Russian and Chinese communication, which has been industrialized. He has successively served as a department level cadre in the Provincial Department of Commerce, the European Department of the Ministry of Commerce, the economic and commercial consult of the Chinese Consulate General in Irkusk, the member of the Standing Committee of the Municipal Committee of Suifenhe City, Heilongjiang Province, and the deputy mayor of the government.

Recognition of Language Resources under the Background of Intelligent Revolution

Abstract
Different from the communicative function, cultural carrier function and cognitive function of language, the resource function of language has attracted more and more attention in recent years. Language resources can derive new industries and turn into productive forces. Therefore, it is of great significance to recognize again the attributes of language resources in the context of today’s intelligent revolution. This paper analyzes the following problems from the cognitive perspective of big data: 1) the nature and attributes of language resources; 2) the functions and categories of language resources; 3) the key points and difficulties in the application of language resources.

Key wordslanguage resource, essence and attribute, function and category, language resource application

Wolfgang Teubert
Dr. Wolfgang Teubert was, until 2000, a senior research fellow at the Institutfür Deutsche Sprache (IDS), Mannheim, Germany. As Head of the Multilingual Research Unit, he was in charge, as the German partner, of important European projects including NERC, PAROLE, SIMPLE, and ELAN. He was the co-ordinator of the Concerted Action TELRI (1995 to 2002), an infrastructure projects involving 40 corpus research centres all over Europe. In 2000, he was appointed to the Chair of Corpus Linguistics, Department of English at the University of Birmingham. The focus of his research is the extraction of linguistic knowledge from real language data, particularly in multilingual environments with the emphasis on semantics. His other interest is the application of the methodology of corpus linguistics to critical discourse analysis. He is also the editor of the International Journal of Corpus Linguistics.

Adverse Aspects of the Digitisation of Discourse

Abstract
It is essentially language that gives us human beings our special position among living beings. Language allows us to escape the loneliness of our thinking and to form a community with other people. With them, we can share our knowledge, preferences and fears; with them, we can collectively construct our reality as we like it by exchanging and discussing our views, thus changing it in such a way that it better conforms to our aspirations. In order to do so, we must be free to speak with each other as we please, without being bound by rules others have enacted with the intention to curtail our voice. Those at the top always had the advantage to grow up in an environment where they learnt the pleasure of taking part in such disputes. They were privileged to develop their creative intelligence from early on. Most others didn’t have this opportunity. The question is whether the current transformation of our society, caused by digitisation, will allow us to reclaim our voice. My rather pessimistic answer is that digitisation, often welcomed as a solution to a multitude of problems, may have an adverse effect on our creativity. It has the very realistic potential of dumbing us down, of turning us all into obedient robots. If I am right, what can we possibly do to counter the danger of the increasing digitization of our language?

CHEN Shengquan
Bill Chen, vice chairman of the 7th Translators Association of China and deputy director of Localization Committee, product manager of Huawei machine translation, and former director of Huawei Translation Services Center. He has been engaged in software programming, computer science teaching, technical writing, translation and localization management for many years, and has been awarded the title of Gold-medal lecturer by Huawei University. He is also an external tutor for Jinan University, Guangdong University of Foreign Studies, Shanghai Jiao Tong University, and The Chinese University of Hong Kong (Shenzhen).

Machine Translation and Human Translation

Abstract
This paper briefly introduces the principle of the RBMT, SMT, and NMT, comparing the advantages and disadvantages of the three systems. Taking Huawei’s actual implementation of MT as an example, the paper will elaborate on the typical scenarios of MT used in multinational enterprises, the prospect of MT development, and suggestions for linguistic research and translation education.

Christina Alexandris
Dr. Christina Alexandris is Associate Professor in Computational Linguistics and German Linguistics at the National and Kapodistrian University of Athens, Greece. She is Head of the Journalism Computational Linguistics Laboratory (JCL Lab) at the National Technical University of Athens (in collaboration with the Danube University Krems, Austria, “Athena”- Research and Innovation Center, Athens, Institution of Promotion of Journalism Ath.Vas. Botsi, Athens). Christina Alexandris has been involved in bilingual and multilingual Computational Linguistics applications since 1995 as a graduate student and Fulbright scholar in the MSc in Computational Linguistics program, Carnegie Mellon University, Pittsburgh PA USA. She has participated in national and EU research projects (1996 – 2009) and collaborated with the Universal Networking Language (UNL) Project of the United Nations, United Nations Research Center, Tokyo, Japan (2010-2015). She is a member of the American Association for the Advancement of Artificial Intelligence (AAAI) since 2015. Her research interests involve linguistic aspects and linguistic issues in Human-Computer Interaction, Speech Technology Applications and Multilingual Applications as well as special applications for Journalism.

Visualizing Pragmatic Features in Spoken Interaction: Intentions, Behavior and Evaluation

Abstract
Interactive and semi-automatic processing facilitates the correct perception and evaluation of pragmatic features in spoken interaction, especially in discussions and interactions beyond a defined agenda and specified protocol, such as interviews and live conversations in Skype or in the Media. Pragmatic features, in particular, indicators of a Speaker’s attitude-behavior and intentions can be visualized in distinctive annotations in generated messages and generated graphic representations. Pragmatic information can be extracted from semantic-linguistic information or a combination of linguistic information with paralinguistic features. The visualization of pragmatic features enables a user-independent evaluation of information content, Speaker behavior and the success or failure of a spoken interaction, including a discussion or interview. This possibility is of particular importance in spoken interaction with non-native speakers of a natural language and when an international public is concerned.

Key wordstopic-tracking, semantic relations, discourse structure, graphic representations, generated messages, paralinguistic features

DENG Yaochen
Yaochen Deng obtained his PhD from Shanghai Jiaotong University in 2007 and then taught in Dalian Maritime University. He is currently professor of Linguistics in Dalian University of Foreign Languages. His research interests center around the application of Corpus Linguistics in Knowledge Discovery and foreign language teaching.

Corpus Linguistics Research in the Era of Artificial Intelligence

Abstract
The flourish of Artificial Intelligence (AI) pushes the development of Corpus Linguistics Research (CLR). In the past decade, a series of new and innovative AI techniques have been increasingly employed in corpus-based investigations, resulting in the progress of CLR from human examinations of a limited number of instances in a small corpus to automatic and intelligent analyses of a vast amount of authentic data by virtue of machine learning and deep learning. The development is particularly evident in the shift from counting the occurrence frequency of specific linguistic forms in the past to focusing on the variability of semantic meanings in different communicative situations. The presentation, on the basis of a brief review of common practice in corpus-based research, aims to illustrate the power and potentials of AI techniques in CLR by reporting on the results of a fine-grained investigation of language variation from a sociolinguistic perspective.

Key wordsCorpus Linguistics Research, Artificial Intelligence, Language Variation, Machine Learning

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COMMENTATORS OF PARALLEL SESSION

GAO Wei
Dr Wei Gao is a professor in languages, cognition and translation at Dalian University. His research interests lie in the area of translation and interpreting, cognitive and neuro-linguistics, and applied translation . He has published on these topics and presented at many international conferences.

LEI Lei
Professor in Applied Linguistics at the School of Foreign Languages, Huazhong University of Science and Technology. His research interests include corpus linguistics, quantitative linguistics, and academic English. He has published extensively in journals such as Applied Linguistics, International Journal of Corpus Linguistics, and Journal of English for Academic Purposes.

DENG Yaochen
Yaochen Deng obtained his PhD from Shanghai Jiaotong University in 2007 and then taught in Dalian Maritime University. He is currently professor of Linguistics in Dalian University of Foreign Languages. His research interests center around the application of Corpus Linguistics in Knowledge Discovery and foreign language teaching.

CHENG Xin
Professor in Applied linguistics at the School of Foreign Languages, Dalian Maritime University. Her research interests lie in the area of science and technology translation, CAT and bilingual education. She has published on these topics and undertaken the relevant research programmes.

Se-Eun Jhang
Dr. Se-Eun Jhang is the director of World Ocean Development Institute at Korea Maritime and Ocean University (KMOU), and editor-in-chief of the Korean Association for Corpus Linguistics (KACL). He is also the director of Maritime Business Communication Research Center at KMOU since 2010. He was the president of the Korean Association of Language Sciences (2015~2017), president of KACL (2015~2016) , and visiting professor at Dalian Maritime University. He had been visiting scholar of Linguistics Department at University of Texas and University of California. He was awarded Minister of Education Citation in 2018 and won the 2018 Albert Nelson Marquis Lifetime Achievement Award. He has been accepted into Marquis Who’s Who in the World both 2018 and 2019. He has presented in many national and international conferences, published in various journals and books.

PARALLEL SESSION 1

Theme: Research on Neural Mechanism of Language Cognition
CommentatorGAO Wei
ChairGAO Yang
Venue301, SFL 

No.

Author

Institution

Title

1

QU Ming

Muroran Institute of Technology

Creation of Moodle-delivered speaking tests for Chinese language classes in Japan

2

ZHUANG Chao

Central China Normal University

构造以认知为基础的动态语法参照评价

3

XIAN Yunqing

Shanghai International Studies University

Conceptual metaphors for artificial-intelligent technologies and the social cognition embedded therein

4

LIU Jiang

Dalian University

基于构式的语法研究基本路径及其内在关系

5

GAO Yang1
Laura Ying LIU2

1Dalian Maritime University

2San Jose State University

人工智能在ESL学习者语言学习过程中的检测及应用:从理论梳理到实践想法

6

WANG Xuelei

Hangzhou Normal University

人工智能时代的话语研究初探

7

RAN Yunyun

Shanghai University Of Engineering Science

自声跟读语音训练系统

8

LONG Fei

Communication University of China

面向计算的汉语因果关系识别

9

WANG Jing
WANG Lixia
ZHAO Baorong

PLA Dalian Naval Academy

真实语料的慕课与语言教学训练中心仿真平台相结合的“海军实用英语”教学

PARALLEL SESSION 2

Theme: Corpus Linguistics Research①
Commentator:LEI Lei
Chair:XU Yingying
Venue:302, SFL

No.

Author

Institution

Title

1

YANG Cheng

Liaoning University

基于CiteSpace的新时代以来广告语言学刊文计量分析

2

ZHAO Tong

Shenyang Pharmaceutical University

以专业英语教学为目的的词汇表创建——以微管蛋白研究方向为例

3

YUE Ming
NING Tao

Zhejiang University

Public discourse analysis in the era of big data — Using WE as an election forecasting index

4

MENG Qingnan

Dalian Maritime University

语义向量空间模型:“seem to V”和“appear to V”构式搭配变化研究的新视野

5

LIU Lu

Nanjing University

Modeling the cross-cultural communication process of terminology with big data analysis: A case study of “ziben (资本, “capital”)”

6

ZHANG Lei

Shanghai Jiao Tong University

COCA和Phrasebank对学术英语写作作用的质性研究

7

CHEN Ge

Peking University

《现代汉语核心语法》MOOC数据分析与挖掘——基于学习者行为的语法难度研究

8

LI Yaoyao

Dalian Maritime University

“一带一路”领域俄语缩略语语料库的构建及应用研究

9

YANG Jiang1
YAN Si1
YAN Linjue2

1Hunan University of Science and Technology
2Guangdong University of Foreign Studies

A measure of syntactic distance

10

GUO Ranran
CAO Jingxiang
HU Guanru

Dalian University of Technology

英语名词数的标记形式与语义关系

11

LIU Kai

Nanjing University

术语传播应用的情感特征计算分析与研究——以“资本主义”为例

12

ZHANG Ruoyang

Northeast Normal University

A dependency grammar based quantitative analysis upon POS-GR pairs among Chinese and English

PARALLEL SESSION 3

Theme: Corpus Linguistics Research②
Commentator:DENG Yaochen
Chair:ZHAO Xiaodong
Venue:303, SFL

No.

Author

Institution

Title

1

WANG Dingming1
GE Xiaoshuai2

1Sichuan Agricultural University
2Shandong Agricultural University

基于语料库的生物学英语句法强度计量研究

2

QIU Le
HU Fengguo

Communication University of China

A quantitative study on the English translation of Chinese DeP

3

WANG Yu

Peking University

基于依存句法与情感矛盾的计算机反语识别研究

4

ZHAO Lijun

Dalian University of Technology

基于BCC语料库的汉语“N长N短”构式解析

5

ZHAO Xiaodong

Dalian Maritime University

A study on the syntactic positions of linking adverbials in Chinese English learners’ writings

6

SUN Boyang
YUE Ming

Zhejiang University

中介语与翻译腔对译出的影响 ——以林语堂为例

7

GONG Qifeng

Nanjing University

Mapping the knowledge graph of “zīběn (资本, capital)” in modern China (1919-2019)

8

LIU Xiao

Dalian Maritime University

基于俄汉术语语料库的语言学术语翻译研究

9

WANG Lin

Zhejiang Gongshang University

Distance and word order between lexical heads and noun dependents in Chinese-English code-switching

10

DONG Xiaona

Nanjing University

探究术语“资本化”的跨语应用特点及其影响因素

11

LIN Jinfeng

Lanzhou University of Technology

俄汉语谚语世界图景中观念[身体]的数理研究

12

XU Jianwei

Zhejiang University

中外期刊实证类论文英文摘要主观性分析

PARALLEL SESSION 4

Theme: Translation Technology Education and Research in the Era of Artificial Intelligence
Commentator:CHENG Xin
Chair:ZHANG Yan
Venue:304, SFL

No.

Author

Institution

Title

1

MAO Wei

Dalian zheyian Translation Service Co., Ltd.

当前国内机器翻译专业领域的发展水平及在MTI笔译教育中的应用

2

ZHOU Xinghua

Nankai University

人工智能在翻译软件中的应用与评价

3

ZHANG Chenxi

Dalian University

CAT课程中译者信息素养的培养

4

LIU Jian

Hengyang Normal University

基于多模态语料库的同声传译语音拖长现象研究

5

Matsunaga Genjiro

Shenzhen University

外语教育的未来像 (Ⅱ) ——装备AI的翻译机器普及后的“后半部分”的未来

6

LIU Runze
HUANG Xinyu

Nanjing University

“第四范式”驱动下术语研究路径创新与中国术语翻译观重塑

7

CHEN Yanxin

Dalian University

从指示照应关系看翻译汉语语篇中的译者态度

8

CAO Jingxiang
LI Yue
HU Guanru

Dalian University of Technology

中医术语的中外译本对比

9

HU Guanru
CAO Jingxiang
GUO Ranran

Dalian University of Technology

中国特色政治术语在外传播与对外传播的比较研究——以“人类命运共同体”为例

10

JIANG Sijia

Nanjing University

术语跨语能产性的大数据分析及其影响因素探讨:以“资本”为例

11

SUN Yulei

Sun Yat-sen University

《伊势物语》现代语译平行语料考察——以第七段《回浪》为例

12

ZHANG Yan
SUN Zhikuan
CHEN Meiyue

Shanghai Maritime University

Translating into topic chains in international laws — A corpus-based study of English-Chinese translation shift

PARALLEL SESSION 5

Theme: Maritime English Education and Research
Commentator:Se-Eun Jhang
Chair:SHI Chaojian      
Venue:Yuexiang Reading Room, 4 Floor, SFL

No.

Author

Institution

Title

1

LI Yan

Dalian Maritime University

Research on maritime English scope for corpus building

2

XU Jin

Dalian Maritime University

将航海类学生领导力培养融入大学英语教学的研究——以大连海事大学为例

3

ZHANG Xiaofeng

Dalian Maritime University

海事英语中的明喻与隐喻研究

4

SUI Guilan
YANG Qi

Dalian Maritime University

Possessory lien, “船舶留置权”还是“占有优先权”?

5

LI Xiaoming

Dalian Maritime University

Maritime English teachers’ pedagogical beliefs on pronunciation strategies

6

WANG Yingli

Dalian Maritime University

慕课《航海英语听力与会话》的设计、开发与应用

学院简介原文链接

        外国语学院的前身是大连海运学院科技外语部。1997年成立外语系,2005年成立外国语学院。

        学院下设英语系、日语系、海上专业大学英语教学部、陆上专业大学英语教学部、、研究生公共外语教学部、西语教学部、外教教学部和语言教学中心等教学机构。设有全球化与外语教学研究中心、英语语言文学研究中心、日语教学研究所等研究机构。学院配备了先进的语言教学设备,拥有19个多媒体教室、14个数字化语音室、2个同传实验室、2个计算机辅助翻译实验室、1个图书资料室,1个音像资料编辑室。学院拥有丰富的专业图书、期刊杂志等教学资源。1998年开始招收英语专业本科生,2005年开始招收日语专业本科生。学院现在校本科生约500人,研究生约200人。

        外国语学院现有英语、日语两个本科专业。英语专业在2012年辽宁省本科专业综合评价中位列全省第三名,2015年获批辽宁省优势特色专业;日语专业在2013年辽宁省本科专业综合评价中位列全省第五名。依托外国语学院多年的办学经验,先进的教学条件和优良的师资队伍,英语和日语专业目前已发展成为特色鲜明的本科专业。

        1985年获批“外国语言学与应用语言学”硕士学位授权点,2005年获批“英语语言文学”硕士学位授权点,2011年获批翻译硕士专业学位授权点。2018年外国语言文学一级学科授权点增列成功。

        2008年“外国语言学与应用语言学”硕士点成为辽宁省重点学科,是国内最早开展语料库语言学和计量语言学研究的为数不多的机构之一。外国语言学及应用语言学硕士点包括海事英语、语料库语言学与机助翻译、英语语言学理论与教学、商务英语4个研究方向。

        英语语言文学硕士点包括翻译学、英美文学2个研究方向。俄语语言文学硕士点包括语言学、俄罗斯文学、翻译学和区域国别研究4个研究方向。日语语言文学硕士点包括语言学、日本文学、翻译学3个研究方向。

        英语笔译和口译硕士点包括海事翻译、机助翻译和商务翻译3个研究方向,日语笔译和口译硕士点包括科技翻译、商务翻译和文学翻译3个研究方向。

        “大学英语研究基地”是辽宁省首批和唯一的外语教育规划重点研究基地。2013年,“大连海事大学—百奥泰国际会议(大连)有限公司文科实践教育基地”获批“辽宁省大学生实践教育基地”建设项目,语言教学中心获批“辽宁省普通高等学校本科实验教学示范中心”建设项目。此外,我们还设有全球化与外语教学研究中心、英语语言文学研究中心、日语教学研究所等研究机构。

        学院师资力量雄厚,现有专任教师118,教授19人(其中三级教授3人,2013年,有两名教授分别当选为教育部英语专业教学指导委员会英语教学指导委员会委员(罗卫华)和航海技术类教学指导委员会委员(张晓峰)),副教授44人。具有博士学位的24人,其中8人获澳大利亚、韩国和日本等国外国语言文学博士学位,16人获上海交通大学、上海外国语大学、南京大学和北京师范大学等国内著名大学外国语言文学博士学位。每年聘请外籍教师20余人,此外,还聘请冯志伟、戴炜栋、王克非、汪洪章、刘海涛、陈国华、王宏印、朱永生等国内知名专家学者为我校讲座、客座教授,定期来校授课、讲学。

        学院积极开展科学研究与学术交流工作,成果丰硕。从“十二五”至今,发表SSCI检索论文10余篇,CSSCI检索论文80余篇;承担校级以上科研、教研项目60余项,其中国家社科基金项目5项,教育部人文社科项目4项,还获得2017年度教育部哲学社会科学研究重大课题攻关项目(中外海洋文化交流历史文献的整理与传播研究)。出版专著18部(其中3部在国外出版社出版),译著30余部。先后聘请语言学、文学、翻译等领域知名学者50余人来校讲学。  

(以上统计数据截止时间为2018年)

会议主题:
人工智能时代的语言学研究

主旨发言主题:
1. 机器翻译与人工智能
2. Semantic Web and Natural Language – Learning by Reading Text
3. 大规模翻译竞赛译文自动评价研究
4. Computational Linguistics Research in the Era of AI
5. 智能革命背景下对语言资源的再认识
6. Adverse Aspects of the Digitisation of Discourse
7. 机器翻译与人工翻译
8. Visualizing Pragmatic Features in Spoken Interaction: Intentions, Behavior and Evaluation
9. 人工智能时代的语料库语言学研究

学者分论坛:
1. 语言认知神经机制研究
2. 语料库语言学研究①
3. 语料库语言学研究②
4. 人工智能时代的翻译技术教学与研究
5. 海事英语教学与研究

会议形式:
主旨发言、学术交流等。会议交流语言为汉语和英语

会议时间及地点:
时间:2019年10月25-27日
地点:大连海事大学

【未经许可, 严禁擅自使用本站视频】TTV 译直播:语言服务专属 » 【回看】第一届“人工智能时代的语言学研究”国际会议
已有 21 条评论 新浪微博
  1. 头像 曾罡_大连海事大学

    我代表大连海事大学外国语学院真诚感谢译直播对本次活动的大力支持,谢谢你们专业的直播服务。

    2019年10月27日 12:55来自移动端4 回复
    • TTV TTV

      谢谢曾教授的认可和信任!

      2019年10月27日 13:05 回复
  2. 头像 oasis

    很好的交流平台

    2019年10月27日 21:49来自iPhone 回复
  3. 头像

    太好了,分论坛也有直播吗

    2019年10月27日 00:30来自移动端 回复
    • TTV TTV

      只直播分论坛 Corpus Linguistics Research①

      2019年10月27日 11:01 回复
  4. 头像 徐斌

    谢谢冯老师

    2019年10月26日 21:55来自移动端 回复
  5. 头像 小娜

    引领数字教育新时尚。

    2019年10月26日 14:35来自移动端 回复
  6. 头像 孔繁义

    太棒了!

    2019年10月26日 12:29来自移动端 回复
  7. 头像 一水

    我在车上看

    2019年10月26日 12:00来自iPhone 回复
  8. 头像 xiaoying

    此安排助推会议网络新模式,给会务组点赞!

    2019年10月26日 11:20来自移动端 回复
  9. 头像 譯眞

    请问有回放吗?

    2019年10月26日 10:06来自iPhone 回复
  10. 头像 catherine

    非常棒的资源。在线观看直播,跟踪前沿。

    2019年10月26日 10:06 回复
  11. 头像 杨静

    现在的会议都这么高大上了吗

    2019年10月26日 10:00来自iPhone 回复
  12. 头像

    在现场的表示很开心啊

    2019年10月26日 09:59来自移动端 回复
  13. 头像 A00大连喜相逢影视传媒13644968077

    网络直播越来越受青睐

    2019年10月26日 08:44来自移动端 回复
  14. 头像 པད་མ་འོད་ཟེར། 白瑪

    高大上啊

    2019年10月25日 22:46来自移动端 回复
  15. 头像 Stella

    在线参与

    2019年10月25日 19:04来自iPhone 回复
  16. 头像 Sarahᐛ Yo

    期待程昕老师邓耀臣老师

    2019年10月23日 10:33来自iPhone2 回复
  17. 头像 艾红娟-lv4

    能直播真是太好了!嘉惠学林泽被后学啊!

    2019年10月23日 10:11来自移动端 回复
  18. TTV TTV

    期待盛会

    2019年10月21日 14:37 回复
  19. 头像 武大社谢群英

    有时间一定参会

    2019年4月30日 08:27来自iPhone 回复

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