It is argued that infants build a foundation for learning about the world through their incidental acquisition of the spatial and temporal regularities surrounding them. A challenge is that learning occurs across multiple contexts whose statistics can greatly differ. Two artificial language studies with 12-month-olds demonstrate that infants come prepared to parse statistics across contexts using the temporal and perceptual features that distinguish one context from another. These results suggest that infants can organize their statistical input with a wider range of features that typically considered. Possible attention, decision making, and memory mechanisms are discussed.

In 1935 the linguist George Kingsley Zipf made a now classic observation about the relationship between a word's length and its frequency: the more frequent a word is, the shorter it tends to be. He claimed that this 'Law of Abbreviation' is a universal structural property of language. The Law of Abbreviation has since been documented in a wide range of human languages, and extended to animal communication systems and even computer programming languages. Zipf hypothesised that this universal design feature arises as a result of individuals optimising form-meaning mappings under competing pressures to communicate accurately but also efficiently - his famous Principle of Least Effort. In this thesis, I present a novel set of studies which provide direct experimental evidence for this explanatory hypothesis. Using a miniature artificial language learning paradigm, I show in Chapter 2 that language users optimise form-meaning mappings in line with the Law of Abbreviation only when pressures for accuracy and efficiency both operate during a communicative task. These results are robust across different methods of data collection: one version of the experiment was run in the lab, and another was run online, using a novel method I developed which allows participants to partake in dyadic interaction through a web-based interface. In Chapter 3, I address the growing body of work suggesting that a word's predictability in context may be an even stronger determiner of its length than its frequency alone. For instance, Piantadosi et al. (2011) show that shorter words have a lower average surprisal (i.e., tend to appear in more predictive contexts) than longer words, in synchronic corpora across many languages. We hypothesise that the same communicative pressures posited by the Principle of Least Effort, when acting on speakers in situations where context manipulates the information content of words, can give rise to these lexical distributions. Adapting the methodology developed in Chapter 2, I show that participants use shorter words in more predictive contexts only when subject to the competing pressures for accurate and efficient communication. In a second experiment, I show that participants are more likely to use shorter words for meanings with a lower average surprisal. These results suggest that communicative pressures acting on individuals during language use can lead to the re-mapping of a lexicon to align with 'Uniform Information Density', the principle that information content ought to be evenly spread across an utterance, such that shorter linguistic units carry less information than longer ones. Over generations, linguistic behaviour such as that observed in the experiments reported here may bring entire lexicons into alignment with the Law of Abbreviation and Uniform Information Density. For this to happen, a diachronic process which leads to permanent lexical change is necessary. However, crucial evidence for this process - decreasing word length as a result of increasing frequency over time - has never before been systematically documented in natural language. In Chapter 4, I conduct the first large-scale diachronic corpus study investigating the relationship between word length and frequency over time, using the Google Books Ngrams corpus and three different word lists covering both English and French. Focusing on words which have both long and short variants (e.g., info/information), I show that the frequency of a word lemma may influence the rate at which the shorter variant gains in popularity. This suggests that the lexicon as a whole may indeed be gradually evolving towards greater efficiency. Taken together, the behavioural and corpus-based evidence presented in this thesis supports the hypothesis that communicative pressures acting on language-users are at least partially responsible for the frequency-length and surprisal-length relationships found universally across lexicons. More generally, the approach taken in this thesis promotes a view of language as, among other things, an evolving, efficient code for information transfer.

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.

Languages are culturally transmitted through a repeated cycle of learning and communicative interaction. These two aspects of cultural transmission impose (at least) three interacting pressures that can shape the evolution of linguistic structure: a pressure for learnability, a pressure for expressivity, and a pressure for coordination amongst users in a linguistic community. This thesis considers how these sometimes competing pressures impact linguistic complexity across cultural time. Using artificial language and iterated learning experimental paradigms, I investigate the conditions under which complexity in morphological and syntactic systems emerges, spreads, and reduces. These experiments illustrate the interaction of transmission, learning and use in hitherto understudied domains - morphosyntax and word order. In a first study (Chapter 2), I report the first iterated learning experiments to investigate the evolution of complexity in compositional structure at the word and sentence level. I demonstrate that a complex meaning space paired with pressures for learnability and communication can result in compositional hierarchical constituent structure, including fixed combinatorial rules of word formation and word order. This structure grants a productive and productively interpretable language and only requires learners to acquire a finite lexicon and a finite set of combinatorial rules (i.e., a grammar). In Chapter 3, I address the unique effect of communicative interaction on linguistic complexity, by removing language learning completely. Speakers use their native language to express novel meanings either in isolation or during communicative interaction. I demonstrate that even in this case, communicative interaction leads to more efficient and overall simpler linguistic systems. These first two studies provide support for the claim that morphological and syntactic complexity are shaped by an overarching drive towards simplicity (or learnability) in language learning and communication. Chapter 4 reports a series of experiments assessing the possibility that the simplicity bias found in the first two studies operates at a different strength depending on the linguistic level. Studies in natural language learning and in pidgin/creole genesis suggest that while morphological variation seems to be highly susceptible to regularisation, variation in other syntactic features, like word order, appears more likely to be reproduced. I test this experimentally by comparing regularisation of unconditioned variation across morphology and word order in the context of artificial language learning. I show that language users in fact regularise unconditioned variation in a similar way across linguistic levels, suggesting that the simplicity bias may be driven by a single, non-level-specific mechanism. Taken together, the experimental evidence presented in this thesis supports the hypothesis that the cultural and cognitive pressures acting on language users during learning and communicative interaction - for learnability, expressivity and coordination - are at least partially responsible for the evolution of linguistic complexity. Specifically, they are responsible for the emergence of linguistic complexity which maximises learnability and communicative efficiency, and for the reduction of complexity which does not. More generally, the approach taken in this thesis promotes a view of complexity in linguistic systems as an evolving variable determined by the biases of language learners and users as languages are culturally transmitted.

This thesis is concerned with structural iconicity and its effects on possessive classification. The Iconicity-of-distance hypothesis argues that the linguistic distance between a possessor and a possessum reflects the conceptual distance, and is therefore smaller in inalienable possession. The role of distance iconicity in language processing was tested using the artificial language learning paradigm. An experiment was designed to investigate whether speakers of Czech will learn an iconically structured grammar better. The experiment conducted with 40 participants did not show significant differences between the two experimental groups. However, the evidence is inconlusive and the data suggest that structural iconicity could influence processing. The results also suggest that speaker of Czech are able to use alienability as a category of language.