Various phonotactic models have been proposed for the prediction of wordlikeness judgements, most of which have focused primarily on segments. This article aims to model wordlikeness judgements when tone is incorporated. We first show how the two major determinants of wordlikeness judgements, i.e. phonotactic probability and neighbourhood density, can be measured when tone is involved. To test the role of the two determinants of wordlikeness judgements in a tone language, judgement data were obtained from speakers of Cantonese. Bayesian modelling was then used to model the judgement data, showing that phonotactic probability, but not neighbourhood density, influences wordlikeness judgements. We also show that phonotactic probability affects the tendency to judge items as absolutely perfect or more or less wordlike, while it does not affect judgements that an item is absolutely not wordlike. Implications of these results for phonotactic modelling and processes involved in wordlikeness judgements are discussed.

中文翻译：

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将语气融入词相似性判断的建模中

已经提出了各种语音模型来预测词相似性判断，其中大多数主要集中在句段上。本文旨在模拟合并音调时的词形判断。我们首先展示了当涉及音调时，如何测量词形判断的两个主要决定因素，即语音概率和邻域密度。为了测试两个词形判断的决定因素在声调语言中的作用，判断数据来自粤语使用者。然后使用贝叶斯模型对判断数据进行建模，表明语音概率而不是邻域密度会影响词相似性判断。我们还表明，语音概率会影响将项目判断为绝对完美或或多或少类似于单词的倾向，而它不影响判断一个项目绝对不是wordlike的。讨论了这些结果对词形判断中涉及的语音建模和过程的影响。