【作者】 张丽娜；

【导师】 于建平；

【作者基本信息】 燕山大学 ， 外国语言学及应用语言学， 2010， 硕士

【摘要】 模糊性是人类语言的本质属性之一,体现于社会生活的各个方面。自1965年美国控制学专家扎德首先提出模糊集合论之后,各个领域便兴起了以数学方法对模糊现象进行的研究。模糊语言学将模糊集合论应用于语言研究。上世纪七十年代起,国外开始了对语言模糊现象的研究,在中国伍铁平先生首次引入了模糊语言学。模糊语言学是一门交叉学科,需要与诸如数学,计算机,认知等邻近学科进行更为紧密的融合。目前,模糊语言学在语义、语法的层面上已经有了大量系统且有深度的分析与研究,但把模糊集合理论与现代计算机技术相结合进行模糊语义推理的研究,至今很少发现。情态表达说话人的一种态度和心理表征,因而语义往往是模糊的。其中,渐变是情态模糊语义的一个重要特征。本研究将情态动词can的语义渐变量化为隶属度,并挑选出可能影响其语义渐变的一组语义及句法特征,采用自适应性模糊神经网络,旨在建立一个高精度的模糊语义推理模型。为了量化各个语言特征,本研究采用Wconcord软件对所需信息变量进行统计并计算相关互信息,然后利用ANFIS工具箱建立模型并选出最优模型。实验结果得出了影响情态动词can词义的句法及语义特征排序。这一排序结果对英语情态动词can的语义学研究,对英语学习者更好地理解情态动词的模糊语义渐变及其影响因素都有着重要的参考价值。同时,对can模糊语义推理的成功建模不但实现了情态动词模糊语义的计算机推理,将语言学家从费时费力的语料库研究工作中解放出来,而且对促进人机有效交流有着深远的理论和实践指导意义。更多还原

【Abstract】 Fuzziness is one of the intrinsic features of natural language and a widely-existing phenomenon in every aspect of human society. Since Fuzzy Set Theory was first proposed by L. A. Zadeh in 1965, a number of researches on fuzziness have been carried out by means of mathematical methods. Fuzzy linguistics applies fuzzy set theory into linguistic studies. Studies and researches on fuzziness in linguistics have begun in 1970s at abroad, while Professor Wu Tieping first introduced fuzzy linguistics to China. Fuzzy semantics, as an interdiscipline, needs to find its closer connection with other adjacent discipline, like math, computer and cognitive science, etc. Currently in this field, much effort has been devoted to systematic studies and researches on semantic and grammatical level. However, few researches on fuzzy sense inference by integrating Fuzzy Set Theory and modern computational techniques have been done so far.Since modality is the mental representation of the speaker’s attitude, the English modal verbs are remarkably indeterminate in their meanings. Gradience is one important feature of the indeterminacy in modal meanings. In this research, the quantification of the grades of membership of the three interrelated meanings of modal verb can is realized and a group of semantic and syntactic features that potentially influence the gradience are selected. This paper aims at establishing a highly accurate model of fuzzy sense inference by means of Adaptive Neuro-Fuzzy Inference System. To realize the quantification of the linguistic features, Woncord software is utilized to do statistics and Mutual Information of related linguistic information is calculated. Thereafter, Adaptive Neuro-Fuzzy Inference System is adopted to set up models among which the optimal one is selected. The experimental results reveal a sequence of influences of different semantic and syntactic features on the meanings of can. This result is a valuable reference for the semantic studies on modal can and a better comprehension of English learners on the semantic gradience of modality and its influencing factors. Meanwhile, the establishment of this inference model does not only realize the computational inference of modal meanings, but also free linguists from massive corpus tagging work for sense inference and promote the intellectualization of effective man-machine exchange.更多还原