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What Is Lexical Proficiency? Some Answers From Computational Models of Speech Data
Author(s) -
CROSSLEY SCOTT A.,
SALSBURY TOM,
McNAMARA DANIELLE S.,
JARVIS SCOTT
Publication year - 2011
Publication title -
tesol quarterly
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.737
H-Index - 91
eISSN - 1545-7249
pISSN - 0039-8322
DOI - 10.5054/tq.2010.244019
Subject(s) - linguistics , computer science , computational linguistics , psychology , natural language processing , computational model , artificial intelligence , philosophy
& Lexical proficiency, as a cognitive construct, is poorly understood. However, lexical proficiency is an important element of language proficiency and fluency, especially for second language (L2) learners. For example, lexical errors are a common cause of L2 miscommunication (Ellis, 1995). Lexical proficiency is also an important attribute of L2 academic achievement (Daller, van Hout, & Treffers-Daller, 2003). Generally speaking, lexical proficiency comprises breadth of knowledge features (i.e., how many words a learner knows), depth of knowledge features (i.e., how well a learner knows a word), and access to core lexical items (i.e., how quickly words can be retrieved or processed; Meara, 2005). Understanding how these features interrelate and which features are important indicators of overall lexical proficiency can provide researchers and teachers with insights into language learning and language structure. Thus, this study investigates the potential for computational indices related to lexical features to predict human evaluations of lexical proficiency. Such an investigation provides us with the opportunity to better understand the construct of lexical proficiency and examine the capacity for computational indices to automatically assess lexical proficiency. Recent investigations into lexical proficiency as both a learner-based and text-based construct have helped illuminate and model the lexical features

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