Connectionist Modeling of Experience-based Effects in Sentence ...

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4.2 Replication of Previous Simulations activation and a penalty for misses (4.5). Hits (correctly activated units): H = False Alarms (incorrectly activated units): F = mi = i∈Gui i∈U ui 0 if ti − ui ≤ 0 ti − ui otherwise Misses (units with underestimated activation): M = i∈G(H + F )mi H GP E = 1 − H + F + M (4.1) (4.2) (4.3) (4.4) (4.5) A Perl routine controlled training and testing of the ten networks and then calculated the region-specific GPEs. The correct functioning of the process will now be validated by the replication of two previous studies. 4.2 Replication of English and German RC Processing I built the model with the parameters specified by MacDonald and Christiansen (2002) and tried to replicate their results (see figure 3.3 for MC02’s results). MC02 report an RC probability of 0.05. However, the replication fitted their data better when the RC probability was set to 0.1. Konieczny and Ruh (2003) also replicated MC02 with an RC probability of 0.1. Figure 4.1 shows the replication result. The pattern of MC02 was more exactly matched in epochs 3, 4, and 5 but the relevant interactions were also found in epochs 1, 2, and 3. Only the training effect on the main verb in the ORC was not very pronounced. The differences were, however, significant. I used the simplified German grammar from Konieczny and Ruh (2003) to replicate their results. Compared to the original study I gained lower error rates for the main verb in both conditions. Additionally the replication showed a significant experience effect in all regions of the SRC, which was not the case in the original. The pattern by region was successfully matched. I will not go into details regarding the two replication studies. They just build the basis for the following simulations, making sure that the model used here has similar properties as the models in MacDonald and Christiansen (2002) and Konieczny and Ruh (2003). 65
GPE 0.0 0.2 0.4 0.6 0.8 1.0 English SRC rep. that attacked the senator praised the judge Region epoch 1 epoch 2 epoch 3 Chapter 4 Two SRN Prediction Studies GPE 0.0 0.2 0.4 0.6 0.8 1.0 English ORC rep. that the sen. attacked praised the judge Region Figure 4.1: Replication of MacDonald and Christiansen (2002) 4.3 RC Extraction in Mandarin 4.3.1 Simulation 1: Regularity Model Parameters The first simulation should assess the degree of the regularity advantage the ORC receives due to its canonical word order. A regularity effect is assessable only when the frequencies of both RC types in the corpora are identical. Therefore the SRC and the ORC received the same probability in the generation grammar. Although the replications were done with an RC probability of 0.1, I used the original value of 0.05, reported in MacDonald and Christiansen (2002), for the Mandarin regularity simulation. Compared to English the Chinese grammar used here is very simple. Setting the RC probability too high could speed up in the learning process in a way that conceals training effects. The Grammar The grammar used to generate the corpora covered simple regular Mandarin SVO sentences as well as SR and OR clauses. Relative clause attachment could happen at every noun with a probability of 0.05. The embedding depth was theoretically unlimited but with the small attachment probability of 0.05 the longest sentence in the corpora had a length of 16 words. The 17-word lexicon consisted of 9 plural and singular nouns, three transitive and four intransitive verbs, of which one (lijie “understand”) belongs to both categories, the relativizer de and the EOS. Note however, that there is no number agreement between nouns and verbs in Mandarin. The full lexicon is given in the Appendix. Note further that in normal Mandarin intransitive 66 epoch 1 epoch 2 epoch 3
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Connectionist Modeling of Experienc
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Acknowledgments I am grateful to Be
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Contents 3.3.4 Summary . . . . . .
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List of Tables 2.1 Languages with s
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Chapter 1 Preliminaries and the ACT
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Chapter 1 Preliminaries (1) a. The
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1.3 Psycholinguistic Aspects Chapte
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Chapter 1 Preliminaries referrentia
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Chapter 1 Preliminaries empirically
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Chapter 1 Preliminaries rial, in Le
Page 21 and 22: Chapter 1 Preliminaries are limited
Page 23 and 24: Chapter 1 Preliminaries predictor.
Page 25 and 26: Chapter 2 Issues in Relative Clause
Page 45 and 46: clear predictions for head-final RC
Page 51 and 52: Reading time [ms] 400 600 800 1000
Page 55 and 56: OUTPUT PUT PLAN Chapter 3 Connectio
Page 57 and 58: Chapter 3 Connectionist Modelling o
Page 63 and 64: German Word Order Chapter 3 Connect
Page 65 and 66: Length-Adjusted Reading Time (ms) C
Page 69 and 70: Chapter 4 Two SRN Prediction Studie
Page 71: 4.1.3 Training and Testing Chapter
Page 75 and 76: (23) [V1 [N1 V2 de ORC ] N2 de SRC
Page 85 and 86: (27) German with commas: a. SRC: S1
Page 87 and 88: 4.4.4 Discussion Chapter 4 Two SRN
Page 91 and 92: Bibliography M. H. Christiansen. Th
Page 93 and 94: Bibliography E. Gibson and J. Thoma
Page 95 and 96: Bibliography J. W. King and M. Kuta
Page 97 and 98: Bibliography F. Reali and M. H. Chr
Page 99 and 100: Appendix A Statistics SRC ORC regio
Page 101 and 102: Appendix B Grammars B.1 English (wr
Page 103 and 104: B.2 German {numREL, Nnom, RC RCpure
Page 105 and 106: B.3 Mandarin Rel : SRC (0.85) | ORC
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