Developing features has been shown crucial to advancing the state-of-the-art in Semantic Role Labeling (SRL). To improve Chinese SRL, we propose a set of additional features, some...
We develop a quantitative method to assess the style of American poems and to visualize a collection of poems in relation to one another. Qualitative poetry criticism helped guide...
: Semantic clustering is important to various fields in the modern information society. In this work we applied the Independent Component Analysis method to the extraction of the f...
This paper investigates syntactic and sub-lexical features in Turkish discriminative language models (DLMs). DLM is a featurebased language modeling approach. It reranks the ASR o...
Ebru Arisoy, Murat Saraclar, Brian Roark, Izhak Sh...
Latent Variable Models (LVM), like the Shared-GPLVM
and the Spectral Latent Variable Model, help mitigate over-
fitting when learning discriminative methods from small or
modera...