DOI: 10.1126/sciadv.aaw2594
Abstract: Language is universal, but it has few indisputably universal characteristics, with cross-linguistic variation being the norm. For example, languages differ greatly in the number of syllables they allow, resulting in large variation in the Shannon information per syllable. Nevertheless, all natural languages allow their speakers to efficiently encode and transmit information. We show here, using quantitative methods on a large cross-linguistic corpus of 17 languages, that the coupling between language-level (information per syllable) and speaker-level (speech rate) properties results in languages encoding similar information rates (~39 bits/s) despite wide differences in each property individually: Languages are more similar in information rates than in Shannon information or speech rate. These findings highlight the intimate feedback loops between languages’ structural properties and their speakers’ neurocognition and biology under communicative pressures. Thus, language is the product of a multiscale communicative niche construction process at the intersection of biology, environment, and culture.Victor Mair comments at Language Log. There's an article in The Atlantic as well.
INTRODUCTION
Language is universally used by all human groups, but it hardly displays undisputable universal characteristics, with a few possible exceptions related to pragmatic and communicative constraints (1, 2). This ubiquity comes with very high levels of variation across the 7000 or so languages (3). For example, linguistic differences between Japanese and English lead to a ratio of 1:11 in their number of distinct syllables. These differences in repertoire size result in large variation in the amount of information they encode per syllable according to Shannon’s theory of communication. Despite those differences, Japanese and English endow their respective speakers with linguistic systems that fulfill equally well one of the most important roles of spoken communication, namely, information transmission. We show here that the interplay between language-specific structural properties (as reflected by the amount of information per syllable) and speaker-level language processing and production [as reflected by speech rate (SR)] leads languages to gravitate around an information rate (IR) of about 39 bits/s. This finding, based on quantitative methods applied to a large cross-linguistic corpus of 17 languages, highlights the intimate feedback loops between languages and their speakers due to communicative pressures. We suggest that this phenomenon is rooted in the human neurocognitive capacity, probably present in our lineage for a long time (4), and that human language can be analyzed as the product of a multiscale communicative and cultural niche construction process involving biology, environment, and culture (5).
Each human language provides its speakers with a communication system that fulfills their needs for transmitting information to their peers. The Uniform Information Density hypothesis (6) and similar approaches [e.g., (7) and (8)] suggested that speakers distribute information along the speech signal following a smooth distribution rather than high-amplitude fluctuations. Compatible with Shannon’s theory, this optimization process guarantees the robust information transmission at a rate close to the channel capacity. We adopt here a quite different perspective, where we compare, across very different languages, the average rates at which information is emitted. This approach enables us to estimate the channel capacity and to assess whether the large differences observed among languages in terms of encoding result in analog differences in channel capacity or, conversely, whether there exist compensating strategies that go beyond the local adaptation operating during speech production. Therefore, we investigate the interaction between information encoding and average SR and, more specifically, whether the variation among languages in IR is regulated by communicative constraints. Thus, does too low an IR hinder communicative efficiency? And, at the other extreme, does pushing it too high incur too heavy physiological and cognitive costs? While a negative correlation between average SR and the informativeness of linguistic constituents has been demonstrated in a small multilanguage corpus (9), the distribution of IRs across human languages is almost totally unknown despite its crucial importance for understanding human spoken communication. While our data here come only from speech production (information encoding), our results, nevertheless, implicitly address also speech perception (information retrieval) and processing, as they are all intimately coupled and coevolve during language acquisition, use, and change (10).
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