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AAAI
2008
15 years 2 months ago
HTN-MAKER: Learning HTNs with Minimal Additional Knowledge Engineering Required
We describe HTN-MAKER, an algorithm for learning hierarchical planning knowledge in the form of decomposition methods for Hierarchical Task Networks (HTNs). HTNMAKER takes as inpu...
Chad Hogg, Héctor Muñoz-Avila, Ugur ...
99
Voted
ACL
2009
14 years 10 months ago
Improving Automatic Speech Recognition for Lectures through Transformation-based Rules Learned from Minimal Data
We demonstrate that transformation-based learning can be used to correct noisy speech recognition transcripts in the lecture domain with an average word error rate reduction of 12...
Cosmin Munteanu, Gerald Penn, Xiaodan Zhu
CVPR
2007
IEEE
16 years 2 months ago
Real-time Gesture Recognition with Minimal Training Requirements and On-line Learning
In this paper, we introduce the semantic network model (SNM), a generalization of the hidden Markov model (HMM) that uses factorization of state transition probabilities to reduce...
Stjepan Rajko, Gang Qian, Todd Ingalls, Jodi James
78
Voted
ACL
2009
14 years 10 months ago
Accurate Learning for Chinese Function Tags from Minimal Features
Data-driven function tag assignment has been studied for English using Penn Treebank data. In this paper, we address the question of whether such method can be applied to other la...
Caixia Yuan, Fuji Ren, Xiaojie Wang
COLING
2002
15 years 6 days ago
Learning Verb Argument Structure from Minimally Annotated Corpora
In this paper we investigate the task of automatically identifying the correct argument structure for a set of verbs. The argument structure of a verb allows us to predict the rel...
Anoop Sarkar, Woottiporn Tripasai