Machine Learning and Cognitive Science of Language Acquisition

Memory-Based models of inflectional morphology acquisition and processing

author: Walter Daelemans, +Center for Dutch Language and Speech, Department of Linguistics, University of Antwerp

Description

Old and recent results using Memory-Based Learning in inflectional morphology (Pinker: fruit fly of psycholinguistics). Memory-based learning with TiMBL: learning is storage. Cases: English and Dutch past tense; more interesting: German plural and Dutch plural. Computational psycholinguistics methodology.

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*Slides*
0:00	Memory-Based Models of inflectional morphology acquisition and processing
0:03	Contents
1:21	Nature of the human language processing architecture
3:33	Machine Learning
5:02	Supervised Learners
8:08	Eager vs Lazy Learning
11:18	Visualizing disjunctivity
12:55	English Past Tense: Words + Rules
14:27	Prasada & Pinker Data
15:07	Memory-Based Alternative
16:22	Prasada & Pinker Data
16:31	Memory-Based Alternative
16:42	Prasada and Pinker Simulation
18:04	Replication Study in Dutch
18:14	Memory-based learning and classification
18:42	Similarity / distance
20:06	The MVDM distance function
20:49	Distance weighted class voting
22:04	Exemplar weighting
22:21	TiMBL http://ilk.uvt.nl/timbl
22:36	Back to Inflectional Morphology: German Plural - part 1
24:11	Back to Inflectional Morphology: German Plural - part 2
24:23	The default status of -s
24:52	Data & Representation
25:18	Feature Relevance Computation
25:36	Clustering on MVDM materices
26:55	Acquisition Data: Summary of previous studies
27:55	Learnability
29:10	MBL simulation
30:38	Bartke, Marcus, Clahsen (1995)
32:19	MBL simulation
32:58	Discussion
34:40	The Dutch plural
35:17	What is the default process in Dutch plural inflection?
35:42	The Dual-Mechanism Model for Dutch Plural Inflection
36:14	Inflecting non-canonical roots
36:35	Methodology: what is a good model?
38:54	MBL model of Dutch plural inflection - part 1
40:10	MBL model of Dutch plural inflection - part 2
40:49	MBL model of Dutch plural inflection - part 3
41:19	Results - part 1
42:03	Results - part 2
42:21	Results - part 3
42:55	Results - part 4
43:25	Results - part 5
44:58	Results - part 6
45:01	Results - part 7
45:34	Results - part 8
45:37	Results - part 10
46:16	Conclusions
47:21	Additional work with TiMBL

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