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南京师范大学客座教授授予仪式暨学术报告会

发布时间:2014-04-08

 

美国罗彻斯特大学脑与认知科学系教授,美国艺术与科学院院士、美国科学促进会AAAS会士、美国认知科学协会会士、美国心理科学协会会士。Tanenhaus教授在1995年创造性提出口语认知范式Visual World Paradigm,该范式成为视觉和语言整合研究的奠基性成果;带领团队在 Science, PNAS, Behavioral and Brain Sciences, Psychological Review, Psychological Science, Cognition, Cognitive Psychology等一流杂志发表100多篇学术论文主持NICHDNIDCD, NSF多项课题曾担任Language and Cognitive Processes, Cognition, Journal of Experimental Psychology: General, Journal of Experimental Psychology: Learning, Memory and Cognition等一流心理学杂志编辑。
演讲主题:
1.     Studying Language Processing using the Visual World Paradigm
(视觉情境范式在语言加工研究中的应用)
时间:423日(周三下午) 14:00-17:00
2.     Real-time Spoken Word Recognition: A Data Explanation Approach
(实时口语词汇认知:基于数据解释的路径)
时间:425日(周五下午) 14:00-17:00
 
南京师范大学随园校区田家炳南楼国际学术报告厅
 办:
南京师范大学心理学院 南京师范大学“老年心理健康协同创新中心”
 
 
 
Studying Language Processing using the Visual World Paradigm
时间:423日(周三下午) 14:00-17:00
报告内容简介:
I will outline the rationale for using eye-movements to study spoken language, using natural tasks with visually co-present displays or real objects. I will begin by discussing how the visual world paradigm allows cognitive scientists to unify two different traditions in language processing: the language-as-product tradition which emphasizes the importance of studying time course and the language-as-action tradition which emphasizes the importance of studying language in natural contexts, including interactive conversation. I’ll review some classic results from my laboratory and outline some important question and issues for the coming decade, where the visual world paradigm will play a central role.
 
Real-time Spoken Word Recognition: A Data Explanation Approach
时间:425日(周五下午) 14:00-17:00
报告内容简介:
For most of the last two decades two classes models have dominated the spoken word recognition literature: (1) pattern recognition models with abstract representations, and (2) exemplar-based pattern recognition models. I will argue for another class of model: “data explanation” models that evaluate hypotheses about the state of the world according to how well those hypotheses predict the observed properties of the perceptual input. I will outline an explanation-based framework in which prediction and learning play a central role and present supporting evidence from two lines of work. The first examines listeners’ use of pre-word onset anticipatory co-articulation. The second examines listeners’ use of “distal prosody” in generating and evaluating lexical hypotheses.
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