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Gradient Exceptionality in Maximum Entropy Grammar with Lexically Specific Constraints

机译:具有词汇特定约束的最大熵语法中的梯度异常

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摘要

The number of exceptions to a phonological generalization appears to gradiently affect its productivity. Generalizations with relatively few exceptions are relatively productive, as measured in tendencies to regularization, as well as in nonce word productions and other pscyholinguistic tasks. Gradient productivity has been previously modeled with probabilistic grammars, including Maximum Entropy Grammar, but they often fail to capture the fixed pronunciations of the existing words in a language, as opposed to nonce words. Lexically specific constraints allow existing words to be produced faithfully, while permitting variation in novel words that are not subject to those constraints. when each word has its own lexically specific version of a constraint, an inverse correlation between the number of exceptions and the degree of productivity is straightforwardly predicted.
机译:语音泛化的例外数量似乎在逐渐影响其生产率。从正规化的趋势以及现时词产生和其他语音语言任务的角度衡量,只有极少数例外的概括是相对有效的。梯度生产力以前已经用概率语法建模,包括最大熵语法,但是它们常常无法捕获现有单词在语言中的固定发音,而不是现时单词。词法特定的约束条件允许忠实地生成现有单词,同时允许不受这些约束条件影响的新颖单词的变化。当每个单词都有其自己的特定于约束的词汇形式时,可以直接预测例外数量与生产率之间的反相关关系。

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  • 入库时间 2022-08-20 21:06:50

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