Learning within- and between-word variation in probabilistic OT grammars
Learning within- and between-word variation in probabilistic OT grammars
复制标题
学习概率 OT 语法中的词内和词间变异
DOI：
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发表时间：
2018
期刊：
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通讯作者：
A. Nazarov
中科院分区：
文献类型：
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作者：
A. Nazarov
本文提出了一种推断变音符号的新方法，用于在最优理论 (OT) 语法中表示词间变异（例外性）（例如，Pater 2000、2010），使得在面对词内变异时推断此类变音符号成为可能。现有的 OT 中的变音符号推断方法（Pater 2010、Becker 2009、Coetzee 2009）基于分类语法学习（Tesar 1995），这使得它们无法处理词内变异。现有的概率 OT 语法推断方法（例如 Boersma 1998）可以很好地处理词内变异，但无法区分异常词和非异常词，并且与 Pater（2010）的主要思想不相容。我证明后一个想法可以与基于希伯来语案例研究的概率语法兼容（Temkin-Martinez 2010），以便可以学习单词内和单词间的变化。
This paper proposes a novel method of inferring diacritics for representing between-word variation (exceptionality) in Optimality Theoretic (OT) grammars (e.g., Pater 2000, 2010) that makes it possible to infer such diacritics in the face of within-word variation. Existing methods of inferring diacritics in OT (Pater 2010, Becker 2009, Coetzee 2009) are based in categorical grammar learning (Tesar 1995), which makes them unable to handle within-word variation. Existing methods of inferring probabilistic OT grammars (e.g., Boersma 1998) handle within-word variation well, but have no provision to distinguish exceptional from non-exceptional words, and are incompatible with the main idea in Pater (2010). I show that this latter idea can be made compatible with probabilistic grammars based on a case study from Hebrew (Temkin-Martinez 2010), so that both within- and between-word variation can be learned.