Magisterarbeit, 2004
133 Seiten, Note: 1,0
This paper explores the phenomenon of anticipation in language processing, specifically focusing on the anticipation of clause-final heads. The research uses neural network simulations to model and investigate this anticipatory behavior.
The paper begins by providing an overview of different complexity measures used in language processing, highlighting the limitations of existing theories and introducing the anticipation hypothesis. Chapter 3 delves into the concept of anticipation, exploring its theoretical foundations and its application in language processing.
Chapter 4 presents empirical evidence supporting the anticipation hypothesis, while Chapter 5 discusses various models of verbal working memory, leading to the introduction of neural networks as a potential alternative.
The core of the paper lies in the detailed presentation of seven simulation series conducted using Simple Recurrent Networks (SRNs). Each series explores a specific aspect of anticipation, providing insights into the mechanisms of SRNs and the nature of anticipation in language processing.
The General Discussion analyzes the results of the simulations, drawing conclusions about the effectiveness of SRNs as a model for anticipation and discussing the implications of the findings for current theories of language processing.
The main keywords and focus topics of this work include: anticipation, clause-final heads, language processing, complexity measures, Simple Recurrent Networks (SRNs), neural network simulations, verbal working memory, integration cost, Dependency Locality Theory (DLT).
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