Projects
From words to meaning: Association networks and semantic processing KU Leuven
The project consists of three parts: (1) to elaborate the existing word association network, (2) to investigate the semantic properties of a network that is constructed from the word association data set and (3) to explore neuropsychological applications of word association data. The first part consists of further developing and enlarging the world’s largest word association data set, in several languages. In the second part, the network’s ...
Extensions and intensions of semantic categories KU Leuven
As Murphy (2002) said, “concepts are the glue that hold our mental world together” (p. 1). People carve up the world into concepts that capture what things are and what properties they have. So in order to understand a novel object, one could compare it with objects that have similar properties, and group them together. For instance, a never-seen object that has fur, four legs, a tail, and the tendency to bark, can be compared to similar ...
Understanding the Multi-Modal World: Towards Multi-Modal Semantics, Information Search and Retrieval. KU Leuven
Search in art image collections based on color semantics Hasselt University
NEPHOLOGICAL SEMANTICS: Using token clouds for meaning detection in variation linguistics KU Leuven
Towards an integrative model of spoken and written word processing in the intact brain and its decline in primary progressive aphasia and neurodegenerative disease KU Leuven
Form and function in usage-based construction grammar: A semantic/pragmatic analysis of clause-internal irrelevance marking in German. Ghent University
German W-immer/auch-connectives occur in universal concessive conditionals, nonspecific free relatives, and elliptical constructions. By analyzing both formal and semantic/pragmatic differences between these constructions, I will demonstrate that a more precise characterization of a construction’s function is required in order to distinguish formally similar constructions in the constructional network and explain subtle differences between ...
Efficient Language Modeling for Automatic Speech Recognition KU Leuven
Since the advent of deep learning, automatic speech recognition (ASR), like many other fields, has advanced significantly. Both the acoustic model and the language model are now based on artificial neural networks which has yielded drastic improvements in recognition accuracy. However, whereas the state-of-the-art acoustic models have been integrated directly into the core of most if not all speech recognizers, the same cannot be said of ...