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author | Karl Berry <karl@freefriends.org> | 2007-03-07 18:04:30 +0000 |
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committer | Karl Berry <karl@freefriends.org> | 2007-03-07 18:04:30 +0000 |
commit | f20e65ef1cfe5fc288f66e7af8abc8477511b36a (patch) | |
tree | 91b4aa04e610a26e189bf47c7c4f79c52a02ea83 /Master/texmf-dist/doc/latex/umthesis/intro.tex | |
parent | dc6e3a2da3acbc5fd7479b801f0b8c5d3d20aa0e (diff) |
new package umthesis (6mar07)
git-svn-id: svn://tug.org/texlive/trunk@4008 c570f23f-e606-0410-a88d-b1316a301751
Diffstat (limited to 'Master/texmf-dist/doc/latex/umthesis/intro.tex')
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diff --git a/Master/texmf-dist/doc/latex/umthesis/intro.tex b/Master/texmf-dist/doc/latex/umthesis/intro.tex new file mode 100644 index 00000000000..f0e2ebd284c --- /dev/null +++ b/Master/texmf-dist/doc/latex/umthesis/intro.tex @@ -0,0 +1,46 @@ +\chapter{The introduction} +Modern research on lexical access began in the 1950's (though +\cite{ColeRudnicky1983} note very similar research performed in the 1890's by +William Chandler Bagley). Several statistical properties of the mental +lexicon have consistently been found to influence how humans process speech. +One of the earliest and most robust findings was that lexical frequency has a +strong influence on lexical access. Repeated research has shown that high +frequency words elicit quicker and more accurate responses than low +frequency words in a large variety of experimental conditions +(e.g.\ \cite{Broadbent1967, Taft1979, BenkiJASA}). Another factor which has +been reliably shown to affect lexical access is neighborhood density. +Neighborhood density is a metric of similarity, roughly defined as the degree +to which a word is similar to others (both phonological and orthographical +measures have been used). Words which have many similar words are said to be +in dense neighborhoods, whereas words which have few similar words are said to +be in sparse neighborhoods. In contrast to lexical frequency, which +facilitates the activation of a word in the brain, neighborhood density has +been found to inhibit activation (e.g.\ \cite{Luce1986, Luce1998, BenkiJASA, +Imai2005}). Of course these are not the only factors which affect language +processing, but they are the most frequently cited, and will be referred to +again in the following sections. +\begin{table*}[!htb] + \centering + \caption[Basic Predictions]{Basic Predictions: Predicted results are marked + with a checkmark, and a relative effect size is also given.} + \label{T:predictions} + \begin{tabularx}{\textwidth}{% + >{\setlength{\hsize}{1.5\hsize}\raggedright\arraybackslash}X% + *{2}{>{\setlength{\hsize}{.7\hsize}\raggedright\arraybackslash}X}% + *{2}{>{\setlength{\hsize}{1.05\hsize}\raggedright\arraybackslash}X}} + \hline\hline + \rule{0em}{1.1em}& English native listeners& German native listeners & + English non-native listeners & German non-native listeners\\[.3em] + \cline{2-5} + \rule{0em}{1.1em}lexical status & \checkmark robust& \checkmark + robust& \checkmark less than native listeners& \checkmark less than native + listeners\\ + morphology & marginal & more than English & less than L1& less than L1\\ + lexical frequency & \checkmark robust& \checkmark + robust& \checkmark less than native listeners& \checkmark less than native + listeners\\ + neighborhood density & \checkmark robust & \checkmark robust & \checkmark less + than L1& \checkmark less than L1\\[.3em] + \hline\hline + \end{tabularx} +\end{table*} |