Many recent proposals claim that languages adapt to their environments. The linguistic niche hypothesis claims that languages with numerous native speakers and substantial proportions of nonnative speakers (societies of strangers) tend to lose grammatical distinctions. In contrast, languages in small, isolated communities should maintain or expand their grammatical markers. Here, we test these claims using a global dataset of grammatical structures, Grambank. We model the impact of the number of native speakers, the proportion of nonnative speakers, the number of linguistic neighbors, and the status of a language on grammatical complexity while controlling for spatial and phylogenetic autocorrelation. We deconstruct “grammatical complexity” into two separate dimensions: how much morphology a language has (“fusion”) and the amount of information obligatorily encoded in the grammar (“informativity”). We find several instances of weak or moderate positive associations but no inverse correlations between grammatical complexity and sociodemographic factors. Our findings cast doubt on the widespread claim that grammatical complexity is shaped by the sociolinguistic environment.

This article investigates to what extent the semantics and the phonological forms of lexical items are genealogically inherited or acquired through language contact. We focus on patterns of colexification (the encoding of two concepts with the same word) as an aspect of lexical-semantic organization. We test two pairs of hypotheses. The first pair concerns the genealogical stability (persistence) and susceptibility to contact-induced change (diffusibility) of colexification patterns and phonological matter in the 40 most genealogically stable elements of the 100-items Swadesh list, which we call “nuclear vocabulary”. We hypothesize that colexification patterns are (a) less persistent, and (b) more diffusible, than the phonological form of nuclear vocabulary. The second pair of hypotheses concerns degrees of diffusibility in two different sections of the lexicon – “core vocabulary” (all 100 elements of the Swadesh list) and its complement (“non-core/peripheral vocabulary”). We hypothesize that the colexification patterns associated with core vocabulary are (a) more persistent, and (b) less diffusible, than colexification patterns associated with peripheral vocabulary. The four hypotheses are tested using the lexical-semantic data from the CLICS database and independently determined phonological dissimilarity measures. The hypothesis that colexification patterns are less persistent than the phonological matter of nuclear vocabulary receives clear support. The hypothesis that colexification patterns are more diffusible than phonological matter receives some support, but a significant difference can only be observed for unrelated languages. The hypothesis that colexification patterns involving core vocabulary are more genealogically stable than colexification patterns at the periphery of the lexicon cannot be confirmed, but the data seem to indicate a higher degree of diffusibility for colexification patterns at the periphery of the lexicon. While we regard the results of our study as valid, we emphasize the tentativeness of our conclusions and point out some limitations as well as desiderata for future research to enable a better understanding of the genealogical versus areal distribution of linguistic features.

Computational textual aesthetics aims at studying observable differences between aesthetic categories of text. We use Approximate Entropy to measure the (un)predictability in two aesthetic text categories, i.e., canonical fiction (‘classics’) and non-canonical fiction (with lower prestige). Approximate Entropy is determined for series derived from sentence-length values and the distribution of part-of-speech-tags in windows of texts. For comparison, we also include a sample of non-fictional texts. Moreover, we use Shannon Entropy to estimate degrees of (un)predictability due to frequency distributions in the entire text. Our results show that the Approximate Entropy values can better differentiate canonical from non-canonical texts compared with Shannon Entropy, which is not true for the classification of fictional vs. expository prose. Canonical and non-canonical texts thus differ in sequential structure, while inter-genre differences are a matter of the overall distribution of local frequencies. We conclude that canonical fictional texts exhibit a higher degree of (sequential) unpredictability compared with non-canonical texts, corresponding to the popular assumption that they are more ‘demanding’ and ‘richer’. In using Approximate Entropy, we propose a new method for text classification in the context of computational textual aesthetics.

Previous research has shown that eyebrow movement during speech exhibits a systematic relationship with intonation: brow raises tend to be aligned with pitch accents, typically preceding them. The present study approaches the question of temporal alignment between brow movement and intonation from a new angle. The study makes use of footage from the Late Night Show with David Letterman, processed with 3D facial landmark detection. Pitch is modeled as a sinusoidal function whose parameters are correlated with the maximum height of the eyebrows in a brow raise. The results confirm some previous findings on audiovisual prosody but lead to new insights as well. First, the shape of the pitch signal in a region of approx. 630 ms before the brow raise is not random and tends to display a specific shape. Second, while being less informative than the post-peak pitch, the pitch signal in the pre-peak region also exhibits correlations with the magnitude of the associated brow raises. Both of these results point to early preparatory action in the speech signal, calling into question the visual-precedes-acoustic assumption. The results are interpreted as supporting a unified view of gesture/speech co-production that regards both signals as manifestations of a single communicative act.