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» Polynomial Conditional Random Fields for Signal Processing
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NIPS
2008
13 years 7 months ago
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
ICASSP
2011
IEEE
12 years 9 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
ICASSP
2010
IEEE
13 years 5 months ago
Language recognition using deep-structured conditional random fields
We present a novel language identification technique using our recently developed deep-structured conditional random fields (CRFs). The deep-structured CRF is a multi-layer CRF mo...
Dong Yu, Shizhen Wang, Zahi Karam, Li Deng
ICASSP
2007
IEEE
13 years 12 months ago
Context-Based Concept Fusion with Boosted Conditional Random Fields
The contextual relationships among different semantic concepts provide important information for automatic concept detection in images/videos. We propose a new context-based conce...
Wei Jiang, Shih-Fu Chang, Alexander C. Loui
ICASSP
2011
IEEE
12 years 9 months ago
Automatic minute generation for parliamentary speech using conditional random fields
We show a novel approach of automatically generating minutes style extractive summaries for parliamentary speech. Minutes are structured summaries consisting of sequences of busin...
Justin Jian Zhang, Pascale Fung, Ricky Ho Yin Chan