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102
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ACL
2006
15 years 3 months ago
Segment-Based Hidden Markov Models for Information Extraction
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
Zhenmei Gu, Nick Cercone
145
Voted
ACL
2012
13 years 4 months ago
Fast Syntactic Analysis for Statistical Language Modeling via Substructure Sharing and Uptraining
Long-span features, such as syntax, can improve language models for tasks such as speech recognition and machine translation. However, these language models can be difficult to u...
Ariya Rastrow, Mark Dredze, Sanjeev Khudanpur
CORR
2000
Springer
129views Education» more  CORR 2000»
15 years 2 months ago
Prosody-Based Automatic Segmentation of Speech into Sentences and Topics
A crucial step in processing speech audio data for information extraction, topic detection, or browsing/playback is to segment the input into sentence and topic units. Speech segm...
Elizabeth Shriberg, Andreas Stolcke, Dilek Z. Hakk...
NLPRS
2001
Springer
15 years 6 months ago
Automatic Segmentation of Words using Syllable Bigram Statistics
We present a syllable bigram model for segmenting a Korean sentence into words and correcting word-spacing errors in the spelling checker. We evaluated the system’s performance ...
Seung-Shik Kang, Chong-Woo Woo
122
Voted
ECCV
2000
Springer
16 years 4 months ago
A Probabilistic Background Model for Tracking
A new probabilistic background model based on a Hidden Markov Model is presented. The hidden states of the model enable discrimination between foreground, background and shadow. Th...
Jens Rittscher, Jien Kato, Sébastien Joga, ...