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21
Induction and interaction in the evolution of language and conceptual structure
Carr, Jon William. - : The University of Edinburgh, 2019
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22
Co-evolution of language and mindreading: a computational exploration
Woensdregt, Marieke Suzanne. - : The University of Edinburgh, 2019
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23
Cross-modal associations and synesthesia: Categorical perception and structure in vowel–color mappings in a large online sample
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24
High-fidelity copying is not necessarily the key to cumulative cultural evolution: a study in monkeys and children
In: Proc Biol Sci (2019)
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25
The emergence of spatial modulation in artificial sign languages ...
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26
Challenges in detecting evolutionary forces in language change using diachronic corpora ...
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27
Quantifying the dynamics of topical fluctuations in language ...
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28
Topical advection as a baseline model for corpus-based lexical dynamics ...
Karjus, Andres; Blythe, Richard A.; Kirby, Simon; Smith, Kenny. - : University of Massachusetts Amherst, 2018
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29
Adult Learning and Language Simplification
Atkinson, Mark; Smith, Kenny; Kirby, Simon. - : John Wiley and Sons Inc., 2018
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30
Simplifying linguistic complexity: culture and cognition in language evolution
Saldana, Carmen Catalina. - : The University of Edinburgh, 2018
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31
Adult Learning and Language Simplification
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32
Topical advection as a baseline model for corpus-based lexical dynamics
In: Proceedings of the Society for Computation in Linguistics (2018)
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33
Animacy Distinctions Arise from Iterated Learning
In: Open Linguistics, Vol 4, Iss 1, Pp 552-565 (2018) (2018)
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34
The cognitive roots of regularization in language ...
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35
Evolutionary psycholinguistic approach to the pragmatics of reference
Bailes, Rachael Louise. - : The University of Edinburgh, 2017
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36
Artificial sign language learning: a method for evolutionary linguistics
Motamedi-Mousavi, Yasamin. - : The University of Edinburgh, 2017
Abstract: Previous research in evolutionary linguistics has made wide use of artificial language learning (ALL) paradigms, where learners are taught artificial languages in laboratory experiments and are subsequently tested in some way about the language they have learnt. The ALL framework has proved particularly useful in the study of the evolution of language, allowing the manipulation of specific linguistic phenomena that cannot be isolated for study in natural languages. Furthermore, this framework can test the output of individual participants, to uncover the cognitive biases of individual learners, but can also be implemented in a cultural evolutionary framework, investigating how participants acquire and change artificial languages in populations where they learn from and interact with each other. In this thesis, I present a novel methodology for studying the evolution of language in experimental populations. In the artificial sign language learning (ASLL) methodology I develop throughout this thesis, participants learn manual signalling systems that are used to interact with other participants. The ASLL methodology combines features of previous ALL methods as well as silent gesture, where hearing participants must communicate using only gesture and no speech. However, ASLL provides several advantages over previous methods. Firstly, reliance on the manual modality reduces the interference of participants’ native languages, exploiting a modality with linguistic potential that is not normally used linguistically by hearing language users. Secondly, research in the manual modality offers comparability with the only current evidence of language emergence and evolution in natural languages: emerging sign languages that have evolved over the last century. Although the silent gesture paradigm also makes use of the manual modality, it has thus far seen little implementation into a cultural evolutionary framework that allows closer modelling of natural languages that are subject to the processes of transmission to new learners and interaction between language users. The implementation and development of ASLL in the present work provides an experimental window onto the cultural evolution of language in the manual modality. I detail a set of experiments that manipulate both linguistic features (investigating category structure and verb constructions) and cultural context, to understand precisely how the processes of interaction and transmission shape language structure. The findings from these experiments offer a more precise understanding of the roles that different cultural mechanisms play in the evolution of language, and further builds a bridge between data collected from natural languages in the early stages of their evolution and the more constrained environments of experimental linguistic research.
Keyword: artificial language learning; artificial sign language learning; evolution of linguistic structure; evolutionary linguistics; language learning
URL: http://hdl.handle.net/1842/23504
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37
Direction and directedness in language change: an evolutionary model of selection by trend-amplification
Stadler, Kevin. - : The University of Edinburgh, 2017
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38
Context, cognition and communication in language
Winters, James Richard. - : The University of Edinburgh, 2017
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39
Minimal requirements for the cultural evolution of language
Spike, Matthew John. - : The University of Edinburgh, 2017
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40
Autopoietic approach to cultural transmission
Papadopoulos-Korfiatis, Alexandros. - : The University of Edinburgh, 2017
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