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EMNLP
2006
15 years 1 months ago
A Hybrid Markov/Semi-Markov Conditional Random Field for Sequence Segmentation
Markov order-1 conditional random fields (CRFs) and semi-Markov CRFs are two popular models for sequence segmentation and labeling. Both models have advantages in terms of the typ...
Galen Andrew
ICASSP
2011
IEEE
14 years 3 months ago
Discriminative duration modeling for speech recognition with segmental conditional random fields
This paper describes a new approach to modeling duration for LVCSR using SCARF, a toolkit for speech recognition with segmental conditional random fields. We utilize SCARF’s abi...
Justine T. Kao, Geoffrey Zweig, Patrick Nguyen
CVPR
2005
IEEE
16 years 1 months ago
Diagram Structure Recognition by Bayesian Conditional Random Fields
Hand-drawn diagrams present a complex recognition problem. Elements of the diagram are often individually ambiguous, and require context to be interpreted. We present a recognitio...
Yuan (Alan) Qi, Martin Szummer, Thomas P. Minka
ICPR
2010
IEEE
15 years 5 months ago
A Meta-Learning Approach to Conditional Random Fields Using Error-Correcting Output Codes
—We present a meta-learning framework for the design of potential functions for Conditional Random Fields. The design of both node potential and edge potential is formulated as a...
Francesco Ciompi, Oriol Pujol, Petia Radeva
IJCNLP
2005
Springer
15 years 5 months ago
Regularisation Techniques for Conditional Random Fields: Parameterised Versus Parameter-Free
Recent work on Conditional Random Fields (CRFs) has demonstrated the need for regularisation when applying these models to real-world NLP data sets. Conventional approaches to regu...
Andrew Smith, Miles Osborne