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<!DOCTYPE html>
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<title>IsCLL-15</title>
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<a href="Crowdsourcing.html">
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<a href="en_Crowdsourcing.html">
<div class="ui inverted orange button">English</div>
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<p style="font-size:15pt;">Crowdsourcing, Word Segmentation, and Semantic Transparency: A new emprical approach to Chinese linguistics</p>
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<a class="header" href="http://llt.cbs.polyu.edu.hk/" style="font-family:Times New Roman;" target="_blank">Chu Ren Huang</a>
<div class="description">Department of Chinese and Bilingual Studies <br> the Hong Kong Polytechnic University</div>
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<p style="font-family:Times New Roman;">Empirical approaches to the scientific studies of language developed rapidly in the last few decades due to the introduction of psychological experiments and electronic corpora. As experiment and measurement tools become more and more sophisticated, and corpora grow bigger and more diversified, new research topics are frequently introduced and exciting discoveries are made. However, regardless of these two successful new directions, we still have not overcome one very basic bottleneck in linguistic research: a reasonably representative sampling size. Language is an ability shared by all human beings and a specific language is a convention of behaviours shared by thousands, even millions, of speakers. So far, the experimental approach can only access the language production data of no more than a few scores of speakers, while it is difficult to rely on corpus sampling to directly capture distributional variations of different speakers. Ideally, linguistic studies should be based on the data produced by a substantial sample of all speakers from different background. The recent development of crowdsourcing research paradigm offers a new and unique opportunity to collect linguistic behavior data from a substantial number of speakers effectively and economically. In this talk, our crowdsourced linguistic studies on word segmentation and semantic transparency will be reported. We will discuss both the methodological adaptation we develop for applying crowdsourcing to Chinese as well as the comparison of results obtained through crowdsourcing with psycholinguistic experiments.</p>
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