We use algorithmic learning and statistical methods over a form frequency list (compiled from the Hungarian web corpus) to investigate variation in Hungarian verbal inflection. Our aims are two-fold: (i) to give an adequate description of this variation, which has not been described in detail in the literature and (ii) to explore the range and depth of lexical attractors that potentially shape this variation. These attractors range from closely related ones, such as the shape of the word form or the behaviour of the verb’s paradigm, to broad ones, such as the behaviour of similar verbs or the phonotactics of related verb forms. We find that verbal variation is predominantly determined by similarity to related verb forms rather than by word shape or by word frequency. What is more, the effect of similarity is better approximated using inflected forms as opposed to base forms as points of comparison. This, in turn, supports a rich memory model of morphology and the mental lexicon1.

中文翻译：

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匈牙利屈折形态变化的吸引子

我们在表格频率列表（由匈牙利网络语料库汇编）上使用算法学习和统计方法来研究匈牙利语言变化的变化。我们的目标有两个：（i）对这种变化进行充分的描述，而文献中没有对此进行详细描述；（ii）探索可能影响这种变化的词汇吸引子的范围和深度。这些吸引子的范围从密切相关的吸引子（例如单词形式的形状或动词范式的行为）到广泛的吸引子（例如类似动词的行为或相关动词形式的变音符）。我们发现，语言变化主要由与相关动词形式的相似性决定，而不是由词的形状或词频决定。更，与基本形式相反，使用变形形式更好地近似相似效果。反过来，这支持形态学和心理词典的丰富记忆模型。