Daniel Freudenthal
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His research interests include the computational simulation of cognitive processes, in particular language acquisition. Recent work has centered around MOSAIC, a computational model that is used to investigate how children’s early multi-word speech is shaped by the statistical properties of the input they hear. The main focus of the simulations revolves around the development of finiteness marking, an issue that has attracted a great deal of Nativist theorizing over the last decade. MOSAIC produces the same types of errors at rates comparable to those in children because it is sensitive to the distributional statistics of the input to which it is exposed in a manner that places great weight on the last items in the speech stream (i.e has an utterance-final bias, or strong recency effect).


flag Simulating Language Acquisition
as author at  Workshop on Machine Learning and Cognitive Science of Language Acquisition, London 2007,