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ICML
2001
IEEE
14 years 8 months ago
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
ECML
2006
Springer
13 years 11 months ago
TildeCRF: Conditional Random Fields for Logical Sequences
Abstract. Conditional Random Fields (CRFs) provide a powerful instrument for labeling sequences. So far, however, CRFs have only been considered for labeling sequences over flat al...
Bernd Gutmann, Kristian Kersting
ACL
2004
13 years 9 months ago
Using Conditional Random Fields to Predict Pitch Accents in Conversational Speech
The detection of prosodic characteristics is an important aspect of both speech synthesis and speech recognition. Correct placement of pitch accents aids in more natural sounding ...
Michelle L. Gregory, Yasemin Altun
ICASSP
2008
IEEE
14 years 2 months ago
A GIS-like training algorithm for log-linear models with hidden variables
Conditional Random Fields (CRFs) are often estimated using an entropy based criterion in combination with Generalized Iterative Scaling (GIS). GIS offers, upon others, the immedi...
Georg Heigold, Thomas Deselaers, Ralf Schlüte...
ECCV
2006
Springer
14 years 9 months ago
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection
This paper introduces the Located Hidden Random Field (LHRF), a conditional model for simultaneous part-based detection and segmentation of objects of a given class. Given a traini...
Ashish Kapoor, John M. Winn