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» Lightly supervised and unsupervised acoustic model training
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NIPS
2001
13 years 10 months ago
Natural Language Grammar Induction Using a Constituent-Context Model
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
Dan Klein, Christopher D. Manning
ACL
2008
13 years 10 months ago
Semi-Supervised Convex Training for Dependency Parsing
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
Qin Iris Wang, Dale Schuurmans, Dekang Lin
KDD
1998
ACM
101views Data Mining» more  KDD 1998»
14 years 23 days ago
Probabilistic Modeling for Information Retrieval with Unsupervised Training Data
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classification of documents based on their relevance to a query. This model was previously...
Ernest P. Chan, Santiago Garcia, Salim Roukos
EMNLP
2008
13 years 10 months ago
Joint Unsupervised Coreference Resolution with Markov Logic
Machine learning approaches to coreference resolution are typically supervised, and require expensive labeled data. Some unsupervised approaches have been proposed (e.g., Haghighi...
Hoifung Poon, Pedro Domingos
ICASSP
2009
IEEE
14 years 12 days ago
Acoustic compensation methods for body transmitted speech conversion
Statistical voice conversion is very effective for enhancing body transmitted speech recorded with Non-Audible Murmur (NAM) microphone. In this method, a probabilistic model to co...
Daisuke Miyamoto, Keigo Nakamura, Tomoki Toda, Hir...