Gareth Roberts

Iconicity has increasingly come to be recognized as widespread in language. It plays a particularly important role in bootstrapping new referring expressions in existing languages and in the emergence of new languages and other communication systems. The basis of this role has long been assumed to depend primarily on transparency of the iconic signal for the receiver, who benefits from being better able to identify its meaning. But might there also be producer-side advantages, distinct from this transparency-based comprehension benefit, that support communication? We investigated this using an experimental referential communication game in which dyads used a novel signaling medium to communicate fruits and vegetables. We manipulated both whether the producer could generate iconic signals and whether the receiver saw iconic or arbitrary signals. Results suggested that there was an iconicity benefit via stability in production even if the receiver was unable to perceive the iconicity (and therefore unable to benefit from transparency). However, while this gave dyads a substantial head-start, the lack of a benefit from iconicity for the receiver meant dyads in this condition still performed significantly less well overall than dyads with full iconicity.

We present an experimental communication game study designed to investigate the effects of noise, context, and time pressures on communication systems. This study is inspired by and follows on from an earlier study, designed to model the emergence of grammatical focus using a simple nonlinguistic communication game paradigm in which participants communicated line figures by selecting cells in a grid to send to each other. In our study, the communication task was more challenging, and a confound between noise and effort pressures was removed. We found that signals became reduced over time, though to a lesser extent given noise, which made communication significantly harder. Time pressures reduced the effect of noise. In general, signals became more stable over time, but noise interfered with the stabilization process. Overall, this study supports the findings of earlier work that employed a much simpler communication task and contributes to our understanding of how information structure gets into language.

How much information do language users need to differentiate potentially absolute synonyms into near-synonyms? How consistent must the information be? We present two simple experiments designed to investigate this. After exposure to two novel verbs, participants generalized them to positive or negative contexts. In Experiment 1, there was a tendency across conditions for the verbs to become differentiated by context, even following inconsistent, random, or neutral information about context during exposure. While a subset of participants matched input probabilities, a high proportion did not. As a consequence, the overall pattern was of growth in differentiation that did not closely track input distributions. Rather, there were two main patterns: When each verb had been presented consistently in a positive or negative context, participants overwhelmingly specialized both verbs in their output. When this was not the case, the verbs tended to become partially differentiated, with one becoming specialized and the other remaining less specialized. Experiment 2 replicated and expanded on Experiment 1 with the addition of a pragmatic judgment task and neutral contexts at test. Its results were consistent with Experiment 1 in supporting the conclusion that quality of input may be more important than quantity in the differentiation of synonyms.

Introduction: Why is it that phonologies exhibit greater dispersion than we might expect by chance? In earlier work we investigated this using a non-linguistic communication game in which pairs of participants sent each other series of colors to communicate a set of animal silhouettes. They found that above-chance levels of dispersion, similar to that seen in vowel systems, emerged as a result of the production and perception demands acting on the participants. However, they did not investigate the process by which this dispersion came about.Method: To investigate this we conducted a secondary statistical analysis of the data, looking in particular at how participants approached the communication task, how dispersion emerged, and what convergence looked like.Results: We found that dispersion was not planned from the start but emerged as a large-scale consequence of smaller-scale choices and adjustments. In particular, participants learned to reproduce colors more reliably over time, paid attention to signaling success, and shifted towards more extreme areas of the space over time.Conclusion: This study sheds light on the role of interactive processes in mediating between human minds and the emergence or larger-scale structure, as well as the distribution of features across the world's languages.

We investigated the emergence of sociolinguistic indexicality using an artificial‐language‐learning paradigm. Sociolinguistic indexicality involves the association of linguistic variants with nonlinguistic social or contextual features. Any linguistic variant can acquire “constellations” of such indexical meanings, though they also exhibit an ordering, with first‐order indices associated with particular speaker groups and higher‐order indices targeting stereotypical attributes of those speakers. Much natural‐language research has been conducted on this phenomenon, but little experimental work has focused on how indexicality emerges. Here, we present three miniature artificial‐language experiments designed to break ground on this question. Results show ready formation of first‐order indexicality based on co‐occurrence alone, with higher‐order indexicality emerging as a result of extension to new speaker groups, modulated by the perceived practical importance of the indexed social feature.

Over half a century ago, George Zipf observed that more frequent words tend to be older. Corpus studies since then have confirmed this pattern, with more frequent words being replaced and regularized less often than less frequent words. Two main hypotheses have been proposed to explain this: that frequent words change less because selection against innovation is stronger at higher frequencies, or that they change less because stochastic drift is stronger at lower frequencies. Here, we report the first experimental test of these hypotheses. Participants were tasked with learning a miniature language consisting of two nouns and two plural markers. Nouns occurred at different frequencies and were subjected to treatments that varied drift and selection. Using a model that accounts for participant heterogeneity, we measured the rate of noun regularization, the strength of selection, and the strength of drift in participant responses. Results suggest that drift alone is sufficient to generate the elevated rate of regularization we observed in low‐frequency nouns, adding to a growing body of evidence that drift may be a major driver of language change.

Language is subject to a variety of pressures. Recent work has documented that many aspects of language structure have properties that appear to be shaped by biases for the efficient communication of semantic meaning. Other work has investigated the role of social pressures, whereby linguistic variants can acquire positive or negative evaluation based on who is perceived to be using them. While the influence of these two sets of biases on language change has been well documented, they have typically been treated separately, in distinct lines of research. We used a miniature language paradigm to test how these biases interact in language change. Specifically, we asked whether pressures to mark social meaning can lead linguistic systems to become less efficient at communicating semantic meaning. We exposed participants to a miniature language with uninformative constituent order and two dialects, one that employed case and one that did not. In the instructions, we socially biased participants toward users of the case dialect, users of the no-case dialect, or neither. Learners biased toward the no-case dialect dropped informative case, thus creating a linguistic system with high message uncertainty. They failed to compensate for this increased message uncertainty even after additional exposure to the novel language. Case was retained in all other conditions. These findings suggest that social biases not only interact with biases for efficient communication in language change but also can lead to linguistic systems that are less efficient at communicating semantic meaning.

Like all modern Celtic languages Welsh exhibits initial consonant mutation with both lexical and morphosyntactic triggers. Owing to the complexity of the system and the sociolinguistic situation of Welsh, change and variation in the system seems inevitable, and evidence for change has been observed in production. Less work, however, has focused on speakers’ attitudes and expectations in perception. We used an online auditory acceptability judgement survey to investigate expectations for different morphosyntactic soft-mutation triggers. Respondents listened to sentences with canonical and non-canonical mutation patterns and used Likert scales to indicate for each sentence whether they would use the same pattern themselves and whether they would expect it from others. Almost all respondents expected some variation, even in their own production, but two main clusters of respondents could be identified: “Conservative” respondents whose expectations were close to canonical mutation patterns and “Variable” respondents whose expectations were considerably more flexible. First-language status was the only demographic variable to predict respondent attitudes, suggesting that L2 Welsh speakers accept noncanonical mutation to a greater extent than L1 Welsh speakers. We also compared different mutation triggers, with the tentative conclusion that apparently identical triggers may not in fact be identical for all speakers, and that trigger transparency may be an important factor in predicting variability.

Significance: Do we talk about some colors more often than others? And do the colors we communicate about most frequently vary across cultures? A classic finding shows that languages around the world partition colors into words in remarkably similar, although not identical, ways. The biology of human color perception helps explain similar color vocabularies across languages, but less is known about how often speakers need to reference different colors. The inference method we develop reveals extensive variation in communicative needs across colors, and a diversity in needs across 130 languages, which helps explain variation in their color vocabularies. Our results open the door to studying cross-cultural variation in demands on different colors, and factors that drive color demands in linguistic communities.

Over half a century ago, George Zipf observed that more frequent words tend to be older. Corpus studies since then have confirmed this pattern, with more frequent words being replaced and regularized less often than less frequent words. Two main hypotheses have been proposed to explain this: that frequent words change less because selection against innovation is stronger at higher frequencies, or that they change less because stochastic drift is stronger at lower frequencies. Here, we report the first experimental test of these hypotheses. Participants were tasked with learning a miniature language consisting of two nouns and two plural markers. Nouns occurred at different frequencies and were subjected to treatments that varied drift and selection. Using a model that accounts for participant heterogeneity, we measured the rate of noun regularization, the strength of selection, and the strength of drift in participant responses. Results suggest that drift alone is sufficient to generate the elevated rate of regularization we observed in low-frequency nouns, adding to a growing body of evidence that drift may be a major driver of language change.