How in-group bias influences the level of detail of speaker-specific information encoded in novel lexical representations

Optionality in animal communication: a novel framework for examining the evolution of arbitrariness

A critical feature of language is that the form of words need not bear any perceptual similarity to their function - these relationships can be 'arbitrary'. The capacity to process these arbitrary form-function associations facilitates the enormous expressive power of language. However, the evolutionary roots of our capacity for arbitrariness, i.e. the extent to which related abilities may be shared with animals, is largely unexamined. We argue this is due to the challenges of applying such an intrinsically linguistic concept to animal communication, and address this by proposing a novel conceptual framework highlighting a key underpinning of linguistic arbitrariness, which is nevertheless applicable to non-human species. Specifically, we focus on the capacity to associate alternative functions with a signal, or alternative signals with a function, a feature we refer to as optionality. We apply this framework to a broad survey of findings from animal communication studies and identify five key dimensions of communicative optionality: signal production, signal adjustment, signal usage, signal combinatoriality and signal perception. We find that optionality is widespread in non-human animals across each of these dimensions, although only humans demonstrate it in all five. Finally, we discuss the relevance of optionality to behavioural and cognitive domains outside of communication. This investigation provides a powerful new conceptual framework for the cross-species investigation of the origins of arbitrariness, and promises to generate original insights into animal communication and language evolution more generally.

People with larger social networks show poorer voice recognition

The way we process language is influenced by our experience. We are more likely to attend to features that proved to be useful in the past. Importantly, the size of individuals’ social network can influence their experience, and consequently, how they process language. In the case of voice recognition, having a larger social network might provide more variable input and thus enhance the ability to recognise new voices. On the other hand, learning to recognise voices is more demanding and less beneficial for people with a larger social network as they have more speakers to learn yet spend less time with each. This paper tests whether social network size influences voice recognition, and if so, in which direction. Native Dutch speakers listed their social network and performed a voice recognition task. Results showed that people with larger social networks were poorer at learning to recognise voices. Experiment 2 replicated the results with a British sample and English stimuli. Experiment 3 showed that the effect does not generalise to voice recognition in an unfamiliar language suggesting that social network size influences attention to the linguistic rather than non-linguistic markers that differentiate speakers. The studies thus show that our social network size influences our inclination to learn speaker-specific patterns in our environment, and consequently, the development of skills that rely on such learned patterns, such as voice recognition.

What Can Network Science Tell Us About Phonology and Language Processing?

Contemporary psycholinguistic models place significant emphasis on the cognitive processes involved in the acquisition, recognition, and production of language but neglect many issues related to the representation of language‐related information in the mental lexicon. In contrast, a central tenet of network science is that the structure of a network influences the processes that operate in that system, making process and representation inextricably connected. Here, we consider how the structure found across phonological networks of several languages from different language families may influence language processing as we age and experience diseases that affect cognition during the typical and atypical acquisition of new words, during typical perception and production of speech in adults, and during language change over time. We conclude that the network science approach may not only provide insights into specific language processes but also provide a way to connect the work from these domains, which are becoming increasingly balkanized.