We present a supervised machine learning algorithm for metonymy resolution, which exploits the similarity between examples of conventional metonymy. We show that syntactic head-mo...
Abstract—Natural language understanding involves the simultaneous consideration of a large number of different sources of information. Traditional methods employed in language an...
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
Human listeners use lexical stress for word segmentation and disambiguation. We look into using lexical stress for speech recognition by examining a Dutch-language corpus. We propo...
We describe a model for the lexical analysis of Arabic text, using the lists of alternatives supplied by a broad-coverage morphological analyzer, SAMA, which include stable lemma ...
Rushin Shah, Paramveer S. Dhillon, Mark Liberman, ...