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ACL
2009
15 years 4 months ago
Learning with Annotation Noise
It is usually assumed that the kind of noise existing in annotated data is random classification noise. Yet there is evidence that differences between annotators are not always ra...
Eyal Beigman, Beata Beigman Klebanov
ICIDS
2010
Springer
15 years 4 months ago
Emohawk: Learning Virtual Characters by Doing
Emohawk is a narrative-based serious game designed to be a supportive tool for teaching basics of virtual agents development at universities and high-schools. Emohawk is built util...
Michal Bída, Cyril Brom
COLING
2010
15 years 1 months ago
Learning Web Query Patterns for Imitating Wikipedia Articles
This paper presents a novel method for acquiring a set of query patterns to retrieve documents containing important information about an entity. Given an existing Wikipedia catego...
Shohei Tanaka, Naoaki Okazaki, Mitsuru Ishizuka
ICASSP
2011
IEEE
14 years 10 months ago
Learning non-parametric models of pronunciation
As more data becomes available for a given speech recognition task, the natural way to improve recognition accuracy is to train larger models. But, while this strategy yields mode...
Brian Hutchinson, Jasha Droppo
ACL
2011
14 years 10 months ago
Can Document Selection Help Semi-supervised Learning? A Case Study On Event Extraction
Annotating training data for event extraction is tedious and labor-intensive. Most current event extraction tasks rely on hundreds of annotated documents, but this is often not en...
Shasha Liao, Ralph Grishman