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COLING
2008
15 years 2 months ago
A Syntactic Time-Series Model for Parsing Fluent and Disfluent Speech
This paper describes an incremental approach to parsing transcribed spontaneous speech containing disfluencies with a Hierarchical Hidden Markov Model (HHMM). This model makes use...
Tim Miller, William Schuler
86
Voted
COLING
2008
15 years 2 months ago
Learning Reliable Information for Dependency Parsing Adaptation
In this paper, we focus on the adaptation problem that has a large labeled data in the source domain and a large but unlabeled data in the target domain. Our aim is to learn relia...
Wenliang Chen, Youzheng Wu, Hitoshi Isahara
104
Voted
EMNLP
2007
15 years 2 months ago
Fast and Robust Multilingual Dependency Parsing with a Generative Latent Variable Model
We use a generative history-based model to predict the most likely derivation of a dependency parse. Our probabilistic model is based on Incremental Sigmoid Belief Networks, a rec...
Ivan Titov, James Henderson
68
Voted
EMNLP
2008
15 years 2 months ago
A Tale of Two Parsers: Investigating and Combining Graph-based and Transition-based Dependency Parsing
Graph-based and transition-based approaches to dependency parsing adopt very different views of the problem, each view having its own strengths and limitations. We study both appr...
Yue Zhang 0004, Stephen Clark
LREC
2008
180views Education» more  LREC 2008»
15 years 2 months ago
MaltEval: an Evaluation and Visualization Tool for Dependency Parsing
This paper presents a freely available evaluation tool for dependency parsing, MaltEval (http://w3.msi.vxu.se/users/jni/malteval). It is flexible and extensible, and provides func...
Jens Nilsson, Joakim Nivre