A Study On Semantic Representation Of Chinese Vocabulary For Speech Therapy

Speech therapy aims to recover efficiency and robustness of patients’ communication function, and therefore it needs to explore mechanisms embedded in semantic system which support the adaptive storage and quick retrieval of semantic information. Speech therapy has another requirement that it must firstly select and arrange language materials. Derived from these two basic requirements, this present study aims to establish a therapy oriented lexical semantic analysis scheme. It was designed to establish an analysis system for classification and quantification of Chinese lexical semantic features. It was also designed to explore network patterns embedded in the lexical semantic system, and then to develop a structural explanation for the quick retrieval and adaptive storage function of lexical semantic processing.This paper reviewed history and current situation of empirical semantic feature datasets. And then, theoretical bases of complex network modeling of semantic features were discussed, which includes several disciplines including Semantic Grammar, Lexical Semantics, Ecological Psychology, Cognitive Science and Network Science. This study also reviewed academic achievements about qualitative and quantitative assessments of semantic features. Inspired by these works, this study designed a classification scheme for Chinese semantic features on the purpose of speech therapy. Theory motivations and case evidences were provided for supporting this classification. This study also designed a framework for establishing empirical Chinese semantic feature norms. By following this framework, Chinese semantic feature norms were established for a small set of living and non-living things. By using datasets of Chinese meta-language and the empirical semantic feature norms, quantitative indexes were calculated for each feature, network models were established for each dataset, and their network parameters were assessed. Based on these analyses, this present study explored cognitive mechanisms of semantic feature analysis. It also revealed four patterns of heterogeneity, small-world, degree mixing and modularity in the network structures of semantic features, so that the efficiency and robustness of semantic feature networks can be explained. Based on these works, this study supported therapy oriented semantic feature norms by literature reviews, basic theory arguments, operation program designs, preliminary data collections, exemplar demonstrations and application perspectives.The main achievement of this study is a speech therapy oriented scheme of analyzing Chinese lexical semantic representation based on cognitive semantic complex network modeling. This scheme has four consecutive building blocks including data collection, feature classification, quantitative indexes calculation and network parameters evaluation. This strategy can generate semantic feature norms with qualitative and quantitative measurements, and then the dataset will be applied to speech therapy.The major innovation of this study is that it introduced networking mindsets and network analysis techniques into lexical semantic researches, and that it established an analysis system for Chinese lexical semantic features with classification and quantification methods. This study has several theoretical contributions. It established theory system for classification of Chinese semantic features. A new vision of medical applications was explored for researches on lexical semantics. A novel speech therapy strategy was introduced with linguistic theoretical consciousness. This study has many application potentials. The semantic feature classification and quantification, and the datasets established by this study, provided novel materials and methods for semantic analysis researches in the linguistic discipline, and also provided new tools and measures for both speech therapy practices and cognitive researches.