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Learning exceptionality and variation with lexically scaled MaxEnt

機器翻譯使用詞匯縮放的maxEnt學習異常和變異

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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;

【作者單位】University of Massachusetts Amherst; University of Massachusetts Amherst; University of Massachusetts Amherst; University of Massachusetts Amherst;

【年(卷),期】2019,,

【頁碼】91-101

【總頁數】11

【正文語種】eng

【中圖分類】;

【關鍵詞】;


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