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Learning exceptionality and variation with lexically scaled MaxEnt

机器翻译使用词汇缩放的maxEnt学习异常和变异

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3.3 【6hr】

【摘要】A growing body of research in phonology addresses the representation and learning of variable processes and exceptional, lexically conditioned processes. Linzen et al. (2013) present a MaxEnt model with additive lexical scales to account for data exhibiting both variation and exceptionality. In this paper, we implement a learning model for lexically scaled MaxEnt grammars which we show to be successful across a range of data containing patterns of variation and exceptionality. We also explore how the model's parameters and the rate of exceptionality in the data influence its performance and predictions for novel forms.

【作者】Coral Hughto; Andrew Lamont; Brandon Prickett; Gaja Jarosz;

【作者单位】University of Massachusetts Amherst; University of Massachusetts Amherst; University of Massachusetts Amherst; University of Massachusetts Amherst;

【年(卷),期】2019,,

【页码】91-101

【总页数】11

【正文语种】eng

【中图分类】;

【关键词】;