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This book addresses universal tendencies of human vowel systems from the point of view of self-organisation. It uses computer simulations to show that the same universal tendencies found in human languages can be reproduced in a population of artificial agents. These agents learn and use vowels with human-like perception and production, using a learning algorithm that is cognitively plausible. The implications of these results for the evolution of language are then explored.

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Humans typically combine linguistic and nonlinguistic information to comprehend emotions. We adopted an emotion identification Stroop task to investigate how different channels interact in emotion communication. In experiment 1, synonyms of “happy” and “sad” were spoken with happy and sad prosody. Participants had more difficulty ignoring prosody than ignoring verbal content. In experiment 2, synonyms of “happy” and “sad” were spoken with happy and sad prosody, while happy or sad faces were displayed. Accuracy was lower when two channels expressed an (...) emotion that was incongruent with the channel participants had to focus on, compared with the cross-channel congruence condition. When participants were required to focus on verbal content, accuracy was significantly lower also when prosody was incongruent with verbal content and face. This suggests that prosody biases emotional verbal content processing, even when conflicting with verbal content and face simultaneously. Implications for multimodal communication and language evolution studies are discussed. (shrink)

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Two computer simulations are investigated that model interaction of cultural evolution of language and biological evolution of adaptations to language. Both are agent‐based models in which a population of agents imitates each other using realistic vowels. The agents evolve under selective pressure for good imitation. In one model, the evolution of the vocal tract is modeled; in the other, a cognitive mechanism for perceiving speech accurately is modeled. In both cases, biological adaptations to using and learning speech evolve, even though (...) the system of speech sounds itself changes at a more rapid time scale than biological evolution. However, the fact that the available acoustic space is used maximally (a self‐organized result of cultural evolution) is constant, and therefore biological evolution does have a stable target. This work shows that when cultural and biological traits are continuous, their co‐evolution may lead to cognitive adaptations that are strong enough to detect empirically. (shrink)

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Temporal regularities in speech, such as interdependencies in the timing of speech events, are thought to scaffold early acquisition of the building blocks in speech. By providing on-line clues to the location and duration of upcoming syllables, temporal structure may aid segmentation and clustering of continuous speech into separable units. This hypothesis tacitly assumes that learners exploit predictability in the temporal structure of speech. Existing measures of speech timing tend to focus on first-order regularities among adjacent units, and are overly (...) sensitive to idiosyncrasies in the data they describe. Here, we compare several statistical methods on a sample of 18 languages, testing whether syllable occurrence is predictable over time. Rather than looking for differences between languages, we aim to find across languages (using clearly defined acoustic, rather than orthographic, measures), temporal predictability in the speech signal which could be exploited by a language learner. First, we analyse distributional regularities using two novel techniques: a Bayesian ideal learner analysis, and a simple distributional measure. Second, we model higher-order temporal structure—regularities arising in an ordered series of syllable timings—testing the hypothesis that non-adjacent temporal structures may explain the gap between subjectively-perceived temporal regularities, and the absence of universally-accepted lower-order objective measures. Together, our analyses provide limited evidence for predictability at different time scales, though higher-order predictability is difficult to reliably infer. We conclude that temporal predictability in speech may well arise from a combination of individually weak perceptual cues at multiple structural levels, but is challenging to pinpoint. (shrink)

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How music and speech evolved is a mystery. Several hypotheses on their origins, including one on their joint origins, have been put forward but rarely tested. Here we report and comment on the first experiment testing the hypothesis that speech and music bifurcated from a common system. We highlight strengths of the reported experiment, point out its relatedness to animal work, and suggest three alternative interpretations of its results. We conclude by sketching a future empirical programme extending this work.

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Arbitrary communication systems can emerge from iconic beginnings through processes of conventionalisation via interaction. Here, we explore whether this process of conventionalisation occurs with continuous, auditory signals. We conducted an artificial signalling experiment. Participants either created signals for themselves, or for a partner in a communication game. We found no evidence that the speech-like signals in our experiment became less iconic or simpler through interaction. We hypothesise that the reason for our results is that when it is difficult to be (...) iconic initially because of the constraints of the modality, then iconicity needs to emerge to enable grounding before conventionalisation can occur. Further, pressures for discrimination, caused by the expanding meaning space in our study, may cause more complexity to emerge, again as a result of the restrictive signalling modality. Our findings have possible implications for the processes of conventionalisation possible in signed and spoken languages, as the spoken modality is more restrictive than the manual modality. (shrink)

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Languages show substantial variability between their speakers, but it is currently unclear how the structure of the communicative network contributes to the patterning of this variability. While previous studies have highlighted the role of network structure in language change, the specific aspects of network structure that shape language variability remain largely unknown. To address this gap, we developed a Bayesian agent‐based model of language evolution, contrasting between two distinct scenarios: language change and language emergence. By isolating the relative effects of (...) specific global network metrics across thousands of simulations, we show that global characteristics of network structure play a critical role in shaping interindividual variation in language, while intraindividual variation is relatively unaffected. We effectively challenge the long‐held belief that size and density are the main network structural factors influencing language variation, and show that path length and clustering coefficient are the main factors driving interindividual variation. In particular, we show that variation is more likely to occur in populations where individuals are not well‐connected to each other. Additionally, variation is more likely to emerge in populations that are structured in small communities. Our study provides potentially important insights into the theoretical mechanisms underlying language variation. (shrink)

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Jackendoff's scenario of the evolution of language is a major contribution towards a more rigorous theory of the origins of language, because it is theoretically constrained by a testable theory of modern language. However, the theoretical constraints from evolutionary theory are not really recognized in his work. We hope that Jackendoff's lead will be followed by intensive cooperation between linguistic theorists and evolutionary modellers.

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