認知科学
Online ISSN : 1881-5995
Print ISSN : 1341-7924
ISSN-L : 1341-7924
特集-新しい計算論が切り拓く認知科学の展開
未分化な文法カテゴリによる幼児発話の誤用
英語の過去形の形態素と日本語の格助詞の過剰生成に共通した計算モデル
河合 祐司大嶋 悠司浅田 稔
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ジャーナル フリー

2017 年 24 巻 1 号 p. 55-76

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抄録
 Young children produce multi-word sentences including some systematic errors or
overproduction. It has been reported that English-speaking children may add a mor-
pheme “ed” to an irregular verb as its past tense while Japanese-speaking children may
position a case particle “NO” after an adjective. We hypothesize that an insufficient in-
crease in grammatical categories causes such overproduction, which can be expected to
disappear with a sufficient increase.We assume that hidden states of a hidden Markov
model (HMM) correspond to grammatical categories acquired from language input.
Based on the HMM, the simulation results could partially verify the above hypothesis.
In the English-trained model, the overproduction could appear and then decline. How-
ever, it did not completely disappear because categories of regular and irregular verbs
did not differentiate even when the model had many categories. In the Japanese-trained
model, the overproduction could appear and then disappear through differentiation of
categories of nouns and adjectives. The limitations of the proposed model are pointed
out and future issues are discussed.
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© 2017 日本認知科学会
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