Context-dependent modelling of deep neural network using logistic regression
10.1109/ASRU.2013.6707753
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sg-nus-scholar.10635-780722015-01-05T21:01:00Z Context-dependent modelling of deep neural network using logistic regression Wang, G. Sim, K.C. COMPUTER SCIENCE Articulatory Features Canonical State Modelling Context-Dependent Modelling Deep Neural Network Logistic Regression 10.1109/ASRU.2013.6707753 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2013 - Proceedings 338-343 2014-07-04T03:12:05Z 2014-07-04T03:12:05Z 2013 Conference Paper Wang, G.,Sim, K.C. (2013). Context-dependent modelling of deep neural network using logistic regression. 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2013 - Proceedings : 338-343. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/ASRU.2013.6707753" target="_blank">https://doi.org/10.1109/ASRU.2013.6707753</a> 9781479927562 http://scholarbank.nus.edu.sg/handle/10635/78072 NOT_IN_WOS Scopus |
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Articulatory Features Canonical State Modelling Context-Dependent Modelling Deep Neural Network Logistic Regression |
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Articulatory Features Canonical State Modelling Context-Dependent Modelling Deep Neural Network Logistic Regression Wang, G. Sim, K.C. Context-dependent modelling of deep neural network using logistic regression |
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10.1109/ASRU.2013.6707753 |
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COMPUTER SCIENCE |
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COMPUTER SCIENCE Wang, G. Sim, K.C. |
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Conference or Workshop Item |
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Wang, G. Sim, K.C. |
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Wang, G. |
title |
Context-dependent modelling of deep neural network using logistic regression |
title_short |
Context-dependent modelling of deep neural network using logistic regression |
title_full |
Context-dependent modelling of deep neural network using logistic regression |
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Context-dependent modelling of deep neural network using logistic regression |
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Context-dependent modelling of deep neural network using logistic regression |
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context-dependent modelling of deep neural network using logistic regression |
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2014 |
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http://scholarbank.nus.edu.sg/handle/10635/78072 |
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