Linking Cognitive and Social Aspects of Sound Change Using Agent‐Based Modeling

Abstract

The paper defines the core components of an interactive-phonetic (IP) sound change model. The starting point for the IP-model is that a phonological category is often skewed phonetically in a certain direction by the production and perception of speech. A prediction of the model is that sound change is likely to come about as a result of perceiving phonetic variants in the direction of the skew and at the probabilistic edge of the listener's phonological category. The results of agent-based computational simulations applied to the sound change in progress, /u/-fronting in Standard Southern British, were consistent with this hypothesis. The model was extended to sound changes involving splits and mergers by using the interaction between the agents to drive the phonological reclassification of perceived speech signals. The simulations showed no evidence of any acoustic change when this extended model was applied to Australian English data in which /s/ has been shown to retract due to coarticulation in /str/ clusters. Some agents nevertheless varied in their phonological categorizations during interaction between /str/ and /Str/: This vacillation may represent the potential for sound change to occur. The general conclusion is that many types of sound change are the outcome of how phonetic distributions are oriented with respect to each other, their association to phonological classes, and how these types of information vary between speakers that happen to interact with each other.

Experience With a Linguistic Variant Affects the Acquisition of Its Sociolinguistic Meaning: An Alien‐Language‐Learning Experiment

“…The same is true for language, where salience and surprisal have been discussed in the context of sentence comprehension (Levy, 2008) and higher‐level systems (Zarcone, Van Schijndel, Vogels, & Demberg, 2016). In sociolinguistics, they are relevant to questions of how variants propagate, and to what degree this process involves selection on the basis of their social meaning or neutral evolution, in which selection is absent and variants propagate through sampling error, mediated by variation in the frequency of interaction (Harrington, Kleber, Reubold, Schiel, & Stevens, 2018; Labov, 2001; Trudgill, 2008, pp. 191, 506; see Roberts, 2013, pp.…”

Perceptual vowel contrast reduction in Australian English /l/-final rimes

“…Perceptual vowel contrast reduction has implications for theories of sound change, as sound change is often related to how coarticulation is produced by the speaker and perceived by the listener (Ohala, 1993;Beddor, 2009;Solé & Ohala, 2010;Ohala, 2012;Garrett & Johnson, 2013;Harrington, Kleber, Reubold, Schiel, & Stevens, 2018). Coarticulation provides systematic and directional variation which may become the input for sound change (Garrett & Johnson, 2013).…”

Associating the origin and spread of sound change using agent-based modelling applied to /s/-retraction in English

“…In the case of /s/-retraction, the sound change is then completed by a merge between a retracted /s/ and /ʃ/. Given that each sub-phonemic unit maps to a unique set of lexical items, then sound change in the IP-model (Harrington et al 2018) is both phonetically and lexically gradual (Bybee 2001;see also Schryver et al 2008 for a discussion and compatible evidence). The possibility is currently being explored of extending split and merge to cases of phonologisation such as the development of contrastive vowel nasalisation from a sequence of an oral vowel and a post-vocalic nasal consonant (Beddor 2015).…”

“…To do so, it uses the ABM architecture developed by Harrington and Schiel (2017), which is an implementation of the interactive-phonetic (IP) model of sound change (Harrington et al 2018). The IP model is defined in Harrington et al (2018) but for the purposes of the present study it is important to outline the minimal set of assumptions about human speech processing and its relationship to the development of sound change from phonetic variation on which the IP model is based. In the IP model, words and phonological classes are statistical models calculated over parameterised stored speech signals.…”