HHU StartFacultiesFaculty of Arts and HumanitiesResearchDFG FOR 2373 “Spoken Morphology”ProjectsDMC: Dutch morphologically complex words: The role of morphology in speech production and comprehension

DMC: Dutch morphologically complex words: The role of morphology in speech production and comprehension

Principal Investigators

Research Assistant

Tim Zee M. A.

Summary

The first phase of the Research Unit has documented traces of a word’s morphological structure in the acoustic signal in English. The goal of this project is to obtain more information about the role of morphology in general and of morpho-phonetic traces in particular in speech processing. So far, we know very little about why and how the speaker produces morpho-phonetic traces and how listeners understand morphologically complex words, produced with or without morpho-phonetic traces. As a consequence, we cannot design full theories of morphological processing.

The project consists of two subprojects. In the first subproject, a PhD student will conduct corpus research and experimental research on morpho-phonetic traces in several registers. In addition, this student will conduct experimental research on whether morpho-phonetic traces may affect speech processing, and if so how. This subproject focusses on Dutch in order to extend the evidence on morphological effects in speech processing to another language and it will thus provide more information about the similarity of these effects across languages.

The second subproject investigates the role of morphology in general, and of morphological acoustic traces in particular, in auditory word comprehension, by investigating what properties a computational model of auditory word comprehension needs to have in order to well simulate human listeners’ processing of morphologically complex words. The focus will be on the computational models that represent two very different types of architecture: DIANA and Naïve Discriminative Learning. The subproject aims at the simulation of human listeners’ behaviour as documented in several existing datasets of word comprehension tasks.

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