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» Lightly supervised and unsupervised acoustic model training
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EMNLP
2009
13 years 6 months ago
Classifier Combination for Contextual Idiom Detection Without Labelled Data
We propose a novel unsupervised approach for distinguishing literal and non-literal use of idiomatic expressions. Our model combines an unsupervised and a supervised classifier. T...
Linlin Li, Caroline Sporleder
CORR
1998
Springer
98views Education» more  CORR 1998»
13 years 8 months ago
Statistical Models for Unsupervised Prepositional Phrase Attachment
We present several unsupervised statistical models for the prepositional phrase attachment task that approach the accuracy of the best supervised methods for this task. Our unsupe...
Adwait Ratnaparkhi
TASLP
2010
133views more  TASLP 2010»
13 years 3 months ago
Unsupervised Equalization of Lombard Effect for Speech Recognition in Noisy Adverse Environments
In the presence of environmental noise, speakers tend to adjust their speech production in an effort to preserve intelligible communication. The noise-induced speech adjustments, c...
Hynek Boril, John H. L. Hansen
TIP
2010
182views more  TIP 2010»
13 years 3 months ago
Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction
We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
ICASSP
2008
IEEE
14 years 3 months ago
A comparative study of probabilistic ranking models for spoken document summarization
The purpose of extractive document summarization is to automatically select a number of indicative sentences, passages, or paragraphs from the original document according to a tar...
Shih-Hsiang Lin, Yi-Ting Chen, Hsin-Min Wang, Bin ...