Different trajectories of morphological overspecification and irregularity under imperfect language learning

Berdičevskis, Aleksandrs; Semenuks, Arturs

doi:10.1093/oso/9780198861287.003.0011

Cited by 5 publications

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“…One possibility is that once the process of simplification is started by the three short-term-learner generations, it will be continued by subsequent generations regardless of their learning time. In other words, long-time learners reproduce the initial languages with complex, but consistent structure rather faithfully, but continue to simplify input languages with inconsistent structure (which may be less overspecified, but also more irregular) [ 76 ].…”

Section: Discussionmentioning

confidence: 99%

Imperfect language learning reduces morphological overspecification: Experimental evidence

Berdičevskis

Semenuks

2022

PLoS ONE

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It is often claimed that languages with more non-native speakers tend to become morphologically simpler, presumably because non-native speakers learn the language imperfectly. A growing number of studies support this claim, but there is a dearth of experiments that evaluate it and the suggested explanatory mechanisms. We performed a large-scale experiment which directly tested whether imperfect language learning simplifies linguistic structure and whether this effect is amplified by iterated learning. Members of 45 transmission chains, each consisting of 10 one-person generations, learned artificial mini-languages and transmitted them to the next generation. Manipulating the learning time showed that when transmission chains contained generations of imperfect learners, the decrease in morphological complexity was more pronounced than when the chains did not contain imperfect learners. The decrease was partial (complexity did not get fully eliminated) and gradual (caused by the accumulation of small simplifying changes). Simplification primarily affected double agent-marking, which is more redundant, arguably more difficult to learn and less salient than other features. The results were not affected by the number of the imperfect-learner generations in the transmission chains. Thus, we provide strong experimental evidence in support of the hypothesis that iterated imperfect learning leads to language simplification.

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Section: Discussionmentioning

confidence: 99%

Imperfect language learning reduces morphological overspecification: Experimental evidence

Berdičevskis

Semenuks

2022

PLoS ONE

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“…Changes introduced by adult learners may spread to others in the population. When native language users have frequent interactions with non-natives, they have a higher probability of adopting [ 23 , 39 , 40 ] and amplifying [ 41 ] simplified forms, and also of producing simpler ‘foreigner directed speech’ [ 31 , 42 ].…”

Section: Introductionmentioning

confidence: 99%

Cumulative cultural evolution, population structure and the origin of combinatoriality in human language

Kirby

Tamariz

2021

Phil. Trans. R. Soc. B

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Language is the primary repository and mediator of human collective knowledge. A central question for evolutionary linguistics is the origin of the combinatorial structure of language (sometimes referred to as duality of patterning), one of language’s basic design features. Emerging sign languages provide a promising arena to study the emergence of language properties. Many, but not all such sign languages exhibit combinatoriality, which generates testable hypotheses about its source. We hypothesize that combinatoriality is the inevitable result of learning biases in cultural transmission, and that population structure explains differences across languages. We construct an agent-based model with population turnover. Bayesian learning agents with a prior preference for compressible languages (modelling a pressure for language learnability) communicate in pairs under pressure to reduce ambiguity. We include two transmission conditions: agents learn the language either from the oldest agent or from an agent in the middle of their lifespan. Results suggest that (1) combinatoriality emerges during iterated cultural transmission under concurrent pressures for simplicity and expressivity and (2) population dynamics affect the rate of evolution, which is faster when agents learn from other learners than when they learn from old individuals. This may explain its absence in some emerging sign languages. We discuss the consequences of this finding for cultural evolution, highlighting the interplay of population-level, functional and cognitive factors. This article is part of a discussion meeting issue ‘The emergence of collective knowledge and cumulative culture in animals, humans and machines’.

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“…Such theories, in our view, are extremely important since they make complexity more than a parameter of cross-linguistic variation: It becomes a meaningful parameter involved in explanatory theories. These theories, if they are correct (which we currently consider an open question), contribute to our understanding of why languages are shaped the way they are, how language change is influenced by social interaction, and how language is organized and functions in the brain (Berdicevskis and Semenuks, 2020).…”

Section: Introductionmentioning

confidence: 99%

Meaning and Measures: Interpreting and Evaluating Complexity Metrics

et al. 2021

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Research on language complexity has been abundant and manifold in the past two decades. Within typology, it has to a very large extent been motivated by the question of whether all languages are equally complex, and if not, which language-external factors affect the distribution of complexity across languages. To address this and other questions, a plethora of different metrics and approaches has been put forward to measure the complexity of languages and language varieties. Against this backdrop we address three major gaps in the literature by discussing statistical, theoretical, and methodological problems related to the interpretation of complexity measures. First, we explore core statistical concepts to assess the meaningfulness of measured differences and distributions in complexity based on two case studies. In other words, we assess whether observed measurements are neither random nor negligible. Second, we discuss the common mismatch between measures and their intended meaning, namely, the fact that absolute complexity measures are often used to address hypotheses on relative complexity. Third, in the absence of a gold standard for complexity metrics, we suggest that existing measures be evaluated by drawing on cognitive methods and relating them to real-world cognitive phenomena. We conclude by highlighting the theoretical and methodological implications for future complexity research.

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Different trajectories of morphological overspecification and irregularity under imperfect language learning

Cited by 5 publications

References 0 publications

Imperfect language learning reduces morphological overspecification: Experimental evidence

Imperfect language learning reduces morphological overspecification: Experimental evidence

Cumulative cultural evolution, population structure and the origin of combinatoriality in human language

Meaning and Measures: Interpreting and Evaluating Complexity Metrics

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