|
|
ix | |
|
|
xi | |
Contributors |
|
xv | |
|
|
|
1 Introduction: Cognitive Issues in Natural Language Processing |
|
|
3 | (24) |
|
|
|
1.1 On the Relationships between Natural Language Processing and Cognitive Sciences |
|
|
3 | (5) |
|
1.2 Recent Issues in Cognitive Aspects of Language Modeling |
|
|
8 | (6) |
|
1.3 Content and Structure of the Book |
|
|
14 | (13) |
|
Part II Models of Neural and Cognitive Processing |
|
|
|
2 Light and Deep Parsing: A Cognitive Model of Sentence Processing |
|
|
27 | (26) |
|
|
|
27 | (1) |
|
2.2 An Interdisciplinary View of Language Processing |
|
|
28 | (11) |
|
2.3 The Theoretical Framework: Property Grammars |
|
|
39 | (3) |
|
2.4 Chunks, Constructions, and Properties |
|
|
42 | (4) |
|
2.5 The Hybrid Architecture |
|
|
46 | (3) |
|
|
49 | (4) |
|
3 Decoding Language from the Brain |
|
|
53 | (28) |
|
|
|
|
|
53 | (2) |
|
3.2 Grounding Language Architecture in the Brain |
|
|
55 | (7) |
|
3.3 Decoding Words in the Brain |
|
|
62 | (4) |
|
|
66 | (2) |
|
|
68 | (4) |
|
|
72 | (9) |
|
4 Graph Theory Applied to Speech: Insights on Cognitive Deficit Diagnosis and Dream Research |
|
|
81 | (20) |
|
|
|
|
|
82 | (2) |
|
4.2 Semantic Analysis for the Diagnosis of Psychosis |
|
|
84 | (1) |
|
4.3 What Is a Speech Graph? |
|
|
85 | (3) |
|
4.4 Speech Graphs as a Strategy to Quantify Symptoms on Psychosis |
|
|
88 | (4) |
|
4.5 Differences in Speech Graphs due to Content (waking × dream reports) |
|
|
92 | (2) |
|
4.6 Speech Graphs Applied to Dementia |
|
|
94 | (2) |
|
|
96 | (5) |
|
Part III Data Driven Models |
|
|
|
5 Putting Linguistics Back into Computational Linguistics |
|
|
101 | (17) |
|
|
5.1 Explicit and Implicit Information |
|
|
101 | (7) |
|
|
108 | (6) |
|
5.3 Linguistic Computation and Computational Linguistics |
|
|
114 | (2) |
|
|
116 | (2) |
|
6 A Distributional Model of Verb-Specific Semantic Roles Inferences |
|
|
118 | (41) |
|
|
|
6.1 Representing and Acquiring Thematic Roles |
|
|
119 | (3) |
|
6.2 Characterizing the Semantic Content of Verb Proto-roles |
|
|
122 | (8) |
|
6.3 A Distributional Model of Thematic Roles |
|
|
130 | (9) |
|
6.4 Experiments with Our Neo-Davidsonian Model |
|
|
139 | (9) |
|
|
148 | (11) |
|
7 Native Language Identification on EFCAMDAT |
|
|
159 | (26) |
|
|
|
|
|
|
|
|
|
159 | (6) |
|
|
165 | (3) |
|
|
168 | (4) |
|
|
172 | (9) |
|
|
181 | (4) |
|
8 Evaluating Language Acquisition Models: A Utility-Based Look at Bayesian Segmentation |
|
|
185 | (42) |
|
|
|
|
185 | (2) |
|
8.2 Early Speech Segmentation |
|
|
187 | (3) |
|
8.3 A Bayesian Segmentation Strategy |
|
|
190 | (6) |
|
8.4 How Well Does This Work Cross-Linguistically? |
|
|
196 | (11) |
|
8.5 How Useful Are the Units? |
|
|
207 | (12) |
|
|
219 | (8) |
|
Part IV Social and Language Evolution |
|
|
|
9 Social Evolution of Public Languages: Between Rousseau's Eden and Hobbes' Leviathan |
|
|
227 | (29) |
|
|
|
227 | (1) |
|
9.2 Is Language a Communication System in the Strong Sense? |
|
|
228 | (5) |
|
9.3 What is the Proper Social Account for the Exaptation of Language for Communication? |
|
|
233 | (17) |
|
|
250 | (6) |
|
10 Genetic Biases in Language: Computer Models and Experimental Approaches |
|
|
256 | (33) |
|
|
|
|
256 | (6) |
|
10.2 Computer Models of Cultural Evolution |
|
|
262 | (16) |
|
|
278 | (3) |
|
|
281 | (8) |
|
11 Transparency versus Processing Efficiency: A Case Study on German Declension |
|
|
289 | (30) |
|
|
|
289 | (1) |
|
11.2 German Declension: Not as Awful as It Seems |
|
|
290 | (10) |
|
11.3 Evaluating the Efficiency of Syncretism |
|
|
300 | (14) |
|
11.4 Discussion and Conclusions |
|
|
314 | (5) |
Index |
|
319 | |