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1
Distinctive feature fusion for recognition of Australian English consonants
In: http://dl.dropboxusercontent.com/u/27743223/200809-Interspeech2008-DistinctiveFeatureFusion.pdf (2008)
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2
D.M.W.: Verb similarity on the taxonomy of WordNet
In: http://david.wardpowers.info/Research/AI/papers/200601-GWC-VerbSimWN.pdf (2006)
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3
A Basis for Compact Distributional Extraction Abstract
In: http://members.dodo.com.au/~powers/Research/AI/papers/199208-THINK-CDE.pdf (2003)
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4
Audio-Visual Speech Recognition using Red Exclusion and Neural Networks
In: http://www.jrpit.flinders.edu.au/confpapers/CRPITV4Lewis.pdf (2003)
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5
AudioVisual Speech Recognition using Red Exclusion and Neural Networks
In: http://ws.acs.org.au/jrpit/JRPIT35.1.41.pdf (2003)
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6
Audio-Visual Speech Recognition using Red Exclusion and Neural Networks
In: http://www.infoeng.flinders.edu.au/papers/20030001.pdf (2003)
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7
Lip Feature Extraction Using Red Exclusion
In: http://www.jrpit.flinders.edu.au/confpapers/CRPITV2Lewis.pdf (2001)
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8
Lip Feature Extraction Using Red Exclusion
In: http://www.cs.flinders.edu.au/Research/AI/papers/200001-VIP-AVSR.pdf (2001)
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9
Learning and Application of Differential Grammars
In: ftp://ai.ist.flinders.edu.au/pub/ai/papers/199703-CoNLL-DG.ps.gz (1997)
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10
System design methodology
In: http://david.wardpowers.info/Research/AI/papers/200603-ACL%2BCoLing-WordSimWN.pdf (1995)
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11
A Multifaceted Investigation into Speech Reading
In: http://members.dodo.com.au/~powers/Research/AI/papers/200108-HIS-MISR.pdf
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12
An empirical evaluation
In: http://www.infoeng.flinders.edu.au/papers/19970003.pdf
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13
Word Sense Disambiguation using lexical cohesion in the context
In: http://acl.ldc.upenn.edu/P/P06/P06-2119.pdf
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14
An Empirical Investigation into Grammatically Constrained Contexts in Predicting Distributional Similarity
In: http://dl.dropboxusercontent.com/u/27743223/200713-ALTW-DistributionalSimilarity.pdf
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15
An Empirical Investigation into Grammatically Constrained Contexts in Predicting Distributional Similarity
In: http://www.alta.asn.au/events/altw2007/cdrom/pdf/ALTA2007_17.pdf
Abstract: The utility of syntactic dependencies in computing distributional similarity has not yet been fully investigated. Most research based on syntactically conditioned co-occurrences simply ignores the salience of grammatical relations and effectively merges syntactic dependencies into one ‘context’. Through calculating distributional similarity, we design two experiments to explore and evaluate the four major types of contexts that are conditioned on grammatical relations. The consistent results show that the headmodifier dependency plays an important role in predicting the semantic features of nouns and verbs, in contrast to other dependencies. 1
URL: http://www.alta.asn.au/events/altw2007/cdrom/pdf/ALTA2007_17.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.222.9864
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16
Smoothing, Normalization, Correction and Reduction
In: http://dl.dropboxusercontent.com/u/27743223/200504-drft-Normalization+LSI+SVD+Katz+TFIDF.pdf
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17
What Unsupervised Learning Tells Us About Language Models
In: ftp://ai.ist.flinders.edu.au/pub/ai/papers/199606-TASL-WULTAL.ps.gz
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18
Smoothing, Normalization, Correction and Reduction
In: http://david.wardpowers.info/Research/AI/papers/200504-drft-Normalization%2BLSI%2BSVD%2BKatz%2BTFIDF.pdf
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19
ROBOT BABIES
In: http://david.wardpowers.info/Research/AI/papers/200106-inv-RBE.pdf
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20
Robot babies: what can they teach us about language acquisition?
In: http://david.wardpowers.info/Research/AI/papers/200004-inv-RBE.pdf
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