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Co-development of action, conceptualization and social interaction mutually scaffold and support each other within a virtuous feedback cycle in the development of human language in children. Within this framework, the purpose of this article is to bring together diverse but complementary accounts of research methods that jointly contribute to our understanding of cognitive development and in particular, language acquisition in robots. Thus, we include research pertaining to developmental robotics, cognitive science, psychology, linguistics and neuroscience, as well as practical computer science and engineering. The different studies are not at this stage all connected into a cohesive whole; rather, they are presented to illuminate the need for multiple different approaches that complement each other in the pursuit of understanding cognitive development in robots. Extensive experiments involving the humanoid robot iCub are reported, while human learning relevant to developmental robotics has also contributed useful results.
Disparate approaches are brought together via common underlying design principles. Without claiming to model human language acquisition directly, we are nonetheless inspired by analogous development in humans and consequently, our investigations include the parallel co-development of action, conceptualization and social interaction. Though these different approaches need to ultimately be integrated into a coherent, unified body of knowledge, progress is currently also being made by pursuing individual methods.
Speakers’ linguistic experience is for the most part experience with language as used in conversational interaction. Though highly relevant for usage-based linguistics, the study of such data is as yet often left to other frameworks such as conversation analysis and interactional linguistics (Couper-Kuhlen and Selting 2001). On the basis of a case study of salient usage patterns of the two German motion verbs kommen and gehen in spontaneous conversation, the present paper argues for a methodological integration of quantitative corpus-linguistic methods with qualitative conversation analytic approaches to further the usage-based study of conversational interaction.
Research on syntactic ambiguity resolution in language comprehension has shown that subjects' processing decisions are influenced by a variety of heterogeneous factors such as e.g., syntactic complexity, semantic fit and the discourse frequency of the competing structures. The present paper investigates a further potentially relevant factor in such processes: effects of syntagmatic lexical chunking (or matching to a complex memorized prefab) whose occurrence would be predicted from usage-based assumptions about linguistic categorisation. Focusing on the widely studied so-called DO/SC-ambiguity in which a post-verbal NP is syntactically ambiguous between a direct object and the subject of an embedded clause, potentially biasing collocational chunks of the relevant type are identified in a number of corpus-linguistic pretests and then investigated in a self-paced reading experiment. The results show a significant increase in processing difficulty from a collocationally neutral over a lexically biasing to a strongly biasing condition. This suggests that syntagmatically complex and partially schematic templates of the kind envisioned in usage-based Construction Grammar may impinge on speakers' online processing decisions during sentence comprehension.
Introduction
(2008)