Christophe Coupé

Approaches to phonological complexity

The proposed volume draws on an interdisciplinary sketch of the phonetics-phonology interface in the light of complexity. Composed of several first-order contributions, it will consequently be a significant landmark at the time of the rise of several projects linking complexity and linguistics around the world.

Human spoken language diversity and the acoustic adaptation hypothesis

Bioacousticians have argued that ecological feedback mechanisms contribute to shaping the acoustic signals of a variety of species and anthropogenic changes in soundscapes have been shown to generate modifications to the spectral envelope of bird songs. Several studies posit that part of the variation in sound structure across spoken human languages could likewise reflect adaptation to the local ecological conditions of their use. Specifically, environments in which higher frequencies are less faithfully transmitted (such as denser vegetation or higher ambient temperatures) may favor greater use of sounds characterized by lower frequencies. Such languages are viewed as “more sonorous.” This paper presents a variety of tests of this hypothesis. Data on segment inventories and syllable structure is taken from LAPSyD, a database on phonological patterns of a large worldwide sample of languages. Correlations are examined with measures of temperature, precipitation, vegetation, and geomorphology reflecting the...

Bridging phonological system and lexicon: Insights from a corpus study of functional load

Abstract In this paper, we propose a functional and cross-language perspective on the organization of phonological systems based on the notion of functional load (FL). Using large corpora, we quantitatively characterize the relationships between phonological components (segments, stress and tones) by estimating their role at the lexical level. In a first analysis, we examine the relative contribution of each phonological subsystem to the pool of lexical distinctions and compare the results between two tonal (Cantonese and Mandarin) and seven non-tonal languages (English, French, German, Italian, Japanese, Korean, and Swahili). The equal weight of vowels and tones in lexical distinction is confirmed as well as the phenomenon of consonantal bias – advocated in several psycholinguistic studies – in five languages (English, French, German, Italian, and Swahili), with various corpus configurations in order to assess the influence of morphology and usage frequency. Our results reflect a strong preference toward consonant-based distinctions rather than vowel-based distinctions in a reduced (lemmatized) configuration of the lexicon. This preference is nevertheless modulated when inflectional morphology and usage frequency were considered. A second analysis consists in a cross-language comparison of the internal FL distribution within vocalic and consonantal subsystems in nine languages. We observe uneven FL distributions with only a few salient high-FL contrasts. Shared trends in terms of the mostly employed phonological features are also revealed but a few language-specific patterns are also present. These results are discussed in terms of organization and processing of the mental lexicon.

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for ‘difficult’ variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we assess a range of candidate distributions, including the Sichel, Delaporte, Box-Cox Green and Cole, and Box-Cox t distributions. We find that the Box-Cox t distribution, with appropriate modeling of its parameters, best fits the conditional distribution of phonemic inventory size. We finally discuss the specificities of phoneme counts, weak effects, and how GAMLSS should be considered for other linguistic variables.

Language Choice in a Multilingual Society: A View from Complexity Science

In addition, for financial support, Lucia Loureiro-Porto thanks the Spanish Ministry for Science and Innovation and the European Regional Development Fund (grant FFI2011-26693-C02-02), while Maxi San Miguel acknowledges financial support from FEDER and MINECO (Spain) under project FIS2012-30634.