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[语言学] 香港理工大学急招语言学博士！项目已拿到funding! [复制链接]

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发表于 2011-12-30 23:20:57 |显示全部楼层

香港理工大学急招语言学博士！研究项目
“Crowdsourcing, Linguistic Analyses, and Language Resources”已拿到funding，
学生可以得到香港理工大学中文及双语学系chair professor Huang Chu-ren,Dr. Angel Chan 及Dr.Yao Yao三位导师的共同指导！有意者请尽快将相关文件（见后面）发到以下邮箱：
hkpucrowdsourcingphd@gmail.com

学系主页：http://www.cbs.polyu.edu.hk/index.php
Professor Huang Chu-ren: http://www.cbs.polyu.edu.hk/staffs/huang-chu-ren.php
Dr. Angel Chan: http://www.cbs.polyu.edu.hk/staffs/CHAN%20Wing%20Shan%20Angel.php
Dr. Yao Yao: http://www.cbs.polyu.edu.hk/staffs/staff-academic.php

以下为相关信息：
PhD Studentship in Linguistics at the Department of Chinese andBilingual Studies, The Hong Kong Polytechnic University
A full-time PhDposition, funded with a 3-year studentship, is available in the Department ofChinese and Bilingual Studies at the Hong Kong Polytechnic University. Thisposition is situated within the project titled “Crowdsourcing, LinguisticAnalyses, and Language Resources”, funded by the Hong Kong Research GrantCouncil’s General Research Fund (GRF), and awarded to Prof Huang Chu Ren (PrincipalInvestigator, Dept of Chinese & Bilingual Studies, The Hong KongPolytechnic University), Dr. Angel Chan and Dr. Yao Yao (co-investigators, Deptof Chinese & Bilingual Studies, The Hong Kong Polytechnic University), Dr.Li, Shoushan (co-investigator, Dept of Computing, Soochow University), and Dr.Li Wenjie (co-investigator, Dept of Computing, The Hong Kong PolytechnicUniversity). The abstract of the project can be found at the end of this posting.
Thedoctoral student will participate actively in project-related research meetingsinvolving an interdisciplinary team of researchers that include faculty,postdocs and students in Linguistics, Psycholinguistics, ComputationalLinguistics, Computer Science and related disciplines. The PhD student is expectedto take an active role in designing, conducting and interpreting a series oflinguistic judgment experiments concerning word segmentation and transparencyof compounds in a Chinese context, using both traditional laboratoryexperiments and crowdsourcing techniques (via the Mechanical Turk).

A native Chinesespeaker with a Master degree in Linguistics, Psychology, Computer Science,Cognitive Science or a related field is required. Background in Linguistics isa prerequisite. Technical experience with or background in psycholinguisticexperimental methodologies and/or crowdsourcing methodologies is preferred.
The position can start in February 2012 or as soon as possiblethereafter. For more information about the postgraduate studentship, please seehttp://www.polyu.edu.hk/fh/PhD/Leaflet.pdf

Candidates shouldsend a CV, samples of English written work, a copy of published papers (ifany), a copy of master degree thesis (if any, or a draft if the thesis is stillin writing), result(s) of public exams such as TOEFL, IELTS, or GRE indicatinglevel of English proficiency, and two to three letters of recommendationelectronically to a special gmail account:
hkpucrowdsourcingphd@gmail.com
Review of applicationswill begin on 15 January 2012 and will continue until the position is filled.
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Abstract of the GRF project “Crowdsourcing,Linguistic Analyses, and Language Resources”

Empirical approaches to the scientific studies of language developedrapidly in the last few decades due to the introduction of psychologicalexperiments and electronic corpora. As experiment and measurement tools becomemore and more sophisticated, and corpora grow bigger and more diversified, newresearch topics are frequently introduced and exciting discoveries are made.However, regardless of these two successful new directions, we still have notovercome one very basic bottleneck in linguistic research: a reasonablyrepresentative sampling size. Language is an ability shared by all human beingsand a specific language is a convention of behaviours shared by thousands, evenmillions, of speakers. So far, the experimental approach can only access thelanguage production data of no more than a few scores of speakers, while corpussampling focuses on variations rather than repetitions. Ideally, linguisticstudies should be based on the data produced by a substantial sample of allspeakers from different background. The recent development of Mechanical Turk(MTurk) offers a new and unique opportunity to collect linguistic behavior datafrom a substantial number of speakers effectively and economically. In this research,we will design three linguistic studies using MTurk and compare the resultswith psycholinguistic experiments and manually corpus annotations in order toexplore the linguistic interpretation, psychological co-relations, andcomputational implementation of this new ‘crowd-sourcing’ approach tolinguistic studies. Results from the study will have implications forlinguistic research as well as for applications such as public opinion miningin the Chinese context.

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