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Neural Models for Predicting Celtic Mutations

机译:预测凯尔特突变的神经模型

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摘要

The Celtic languages share a common linguistic phenomenon known as initial mutations; these consist of pronunciation and spelling changes that occur at the beginning of some words, triggered in certain semantic or syntactic contexts. Initial mutations occur quite frequently and all non-trivial NLP systems for the Celtic languages must learn to handle them properly. In this paper we describe and evaluate neural network models for predicting mutations in two of the six Celtic languages: Irish and Scottish Gaelic. We also discuss applications of these models to grammatical error detection and language modeling.
机译:凯尔特人的语言共有一种常见的语言现象,即初始突变。这些包括在某些单词的开头出现的发音和拼写更改,这些更改是在某些语义或句法上下文中触发的。最初的突变经常发生,凯尔特语的所有非平凡的NLP系统都必须学会正确地处理它们。在本文中,我们描述和评估了用于预测六种凯尔特语中的两种语言的突变的神经网络模型:爱尔兰盖尔语和苏格兰盖尔语。我们还将讨论这些模型在语法错误检测和语言建模中的应用。

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