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ACL
2011
12 years 10 months ago
Automated Whole Sentence Grammar Correction Using a Noisy Channel Model
Automated grammar correction techniques have seen improvement over the years, but there is still much room for increased performance. Current correction techniques mainly focus on...
Y. Albert Park, Roger Levy
ICDAR
2007
IEEE
14 years 17 days ago
Context-Sensitive Error Correction: Using Topic Models to Improve OCR
Modern optical character recognition software relies on human interaction to correct misrecognized characters. Even though the software often reliably identifies low-confidence ...
Michael L. Wick, Michael G. Ross, Erik G. Learned-...
NAACL
2010
13 years 4 months ago
Taxonomy Learning Using Word Sense Induction
Taxonomies are an important resource for a variety of Natural Language Processing (NLP) applications. Despite this, the current stateof-the-art methods in taxonomy learning have d...
Ioannis P. Klapaftis, Suresh Manandhar
ECML
1987
Springer
13 years 9 months ago
Induction in Noisy Domains
This paper examines the induction of classification rules from examples using real-world data. Real-world data is almost always characterized by two features, which are important ...
Peter Clark, Tim Niblett
ACL
2009
13 years 4 months ago
Improving Automatic Speech Recognition for Lectures through Transformation-based Rules Learned from Minimal Data
We demonstrate that transformation-based learning can be used to correct noisy speech recognition transcripts in the lecture domain with an average word error rate reduction of 12...
Cosmin Munteanu, Gerald Penn, Xiaodan Zhu