Cutting the Gordian Knot: The Moving-Average Type-Token Ratio (MATTR)

被引:259
作者
Covington, Michael A. [1 ]
McFall, Joe D. [1 ]
机构
[1] Univ Georgia, Inst Artificial Intelligence, Athens, GA 30602 USA
关键词
ORAL LANGUAGE; CHILDREN;
D O I
10.1080/09296171003643098
中图分类号
H0 [语言学];
学科分类号
030303 ; 0501 ; 050102 ;
摘要
Type-token ratio (TTR), or vocabulary size divided by text length (V/N), is a time-honoured but unsatisfactory measure of lexical diversity. The problem is that the TTR of a text sample is affected by its length. We present an algorithm for rapidly computing TTR through a moving window that is independent of text length, and we demonstrate that this measurement can detect changes within a text as well as differences between texts.
引用
收藏
页码:94 / 100
页数:7
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