自然语言音系的贝叶斯模型:从基础形式生成替代

Special Interest Group on Computational Morphology and Phonology Workshop Pub Date : 2008-06-19 DOI:10.3115/1626324.1626327

David Ellis

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引用次数: 1

摘要

学习音韵学的随机方法。所提出的模型比简单的多数解决方案多捕获了7- 15%的语音上似是而非的潜在形式，因为它更喜欢“纯粹”的替代。在需要近似解的情况下，或者作为更复杂模型的种子，它可能很有用。类似的过程可能涉及儿童语言习得的某些阶段;尤其是语音战术的早期学习。

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A Bayesian Model of Natural Language Phonology: Generating Alternations from Underlying Forms

A stochastic approach to learning phonology. The model presented captures 7--15% more phonologically plausible underlying forms than a simple majority solution, because it prefers "pure" alternations. It could be useful in cases where an approximate solution is needed, or as a seed for more complex models. A similar process could be involved in some stages of child language acquisition; in particular, early learning of phonotactics.

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Special Interest Group on Computational Morphology and Phonology Workshop

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