Dated language phylogenies shed light on the ancestry of Sino-Tibetan.

The Sino-Tibetan language family is one of the world's largest and most prominent families, spoken by nearly 1.4 billion people. Despite the importance of the Sino-Tibetan languages, their prehistory remains controversial, with ongoing debate about when and where they originated. To shed light on this debate we develop a database of comparative linguistic data, and apply the linguistic comparative method to identify sound correspondences and establish cognates. We then use phylogenetic methods to infer the relationships among these languages and estimate the age of their origin and homeland. Our findings point to Sino-Tibetan originating with north Chinese millet farmers around 7200 B.P. and suggest a link to the late Cishan and the early Yangshao cultures.

Linking norms, ratings, and relations of words and concepts across multiple language varieties.

Psychologists and linguists collect various data on word and concept properties. In psychology, scholars have accumulated norms and ratings for a large number of words in languages with many speakers. In linguistics, scholars have accumulated cross-linguistic information about the relations between words and concepts. Until now, however, there have been no efforts to combine information from the two fields, which would allow comparison of psychological and linguistic properties across different languages. The Database of Cross-Linguistic Norms, Ratings, and Relations for Words and Concepts (NoRaRe) is the first attempt to close this gap. Building on a reference catalog that offers standardization of concepts used in historical and typological language comparison, it integrates data from psychology and linguistics, collected from 98 data sets, covering 65 unique properties for 40 languages. The database is curated with the help of manual, automated, semi-automated workflows and uses a software API to control and access the data. The database is accessible via a web application, the software API, or using scripting languages. In this study, we present how the database is structured, how it can be extended, and how we control the quality of the data curation process. To illustrate its application, we present three case studies that test the validity of our approach, the accuracy of our workflows, and the integrative potential of the database. Due to regular version updates, the NoRaRe database has the potential to advance research in psychology and linguistics by offering researchers an integrated perspective on both fields.

Networks of lexical borrowing and lateral gene transfer in language and genome evolution.

Like biological species, languages change over time. As noted by Darwin, there are many parallels between language evolution and biological evolution. Insights into these parallels have also undergone change in the past 150 years. Just like genes, words change over time, and language evolution can be likened to genome evolution accordingly, but what kind of evolution? There are fundamental differences between eukaryotic and prokaryotic evolution. In the former, natural variation entails the gradual accumulation of minor mutations in alleles. In the latter, lateral gene transfer is an integral mechanism of natural variation. The study of language evolution using biological methods has attracted much interest of late, most approaches focusing on language tree construction. These approaches may underestimate the important role that borrowing plays in language evolution. Network approaches that were originally designed to study lateral gene transfer may provide more realistic insights into the complexities of language evolution.

Universal and cultural factors shape body part vocabularies.

Every human has a body. Yet, languages differ in how they divide the body into parts to name them. While universal naming strategies exist, there is also variation in the vocabularies of body parts across languages. In this study, we investigate the similarities and differences in naming two separate body parts with one word, i.e., colexifications. We use a computational approach to create networks of body part vocabularies across languages. The analyses focus on body part networks in large language families, on perceptual features that lead to colexifications of body parts, and on a comparison of network structures in different semantic domains. Our results show that adjacent body parts are colexified frequently. However, preferences for perceptual features such as shape and function lead to variations in body part vocabularies. In addition, body part colexification networks are less varied across language families than networks in the semantic domains of emotion and colour. The study presents the first large-scale comparison of body part vocabularies in 1,028 language varieties and provides important insights into the variability of a universal human domain.

A comparative wordlist for investigating distant relations among languages in Lowland South America.

The history of the language families in Lowland South America remains an understudied area of historical linguistics. Panoan and Tacanan, two language families from this area, have frequently been proposed to descend from the same ancestor. Despite ample evidence in favor of this hypothesis, not all scholars accept it as proven beyond doubt. We compiled a new lexical questionnaire with 501 basic concepts to investigate the genetic relation between Panoan and Tacanan languages. The dataset includes data from twelve Panoan, five Tacanan, and four other languages which have previously been suggested to be related to Pano-Tacanan. Through the transparent annotation of grammatical morphemes and partial cognates, our dataset provides the basis for testing language relationships both qualitatively and quantitatively. The data is not only relevant for the investigation of the ancestry of Panoan and Tacanan languages. Reflecting the state of the art in computer-assisted approaches for historical language comparison, it can serve as a role model for linguistic studies in other areas of the world.

Grouping sounds into evolving units for the purpose of historical language comparison.

Computer-assisted approaches to historical language comparison have made great progress during the past two decades. Scholars can now routinely use computational tools to annotate cognate sets, align words, and search for regularly recurring sound correspondences. However, computational approaches still suffer from a very rigid sequence model of the form part of the linguistic sign, in which words and morphemes are segmented into fixed sound units which cannot be modified. In order to bring the representation of sound sequences in computational historical linguistics closer to the research practice of scholars who apply the traditional comparative method, we introduce improved sound sequence representations in which individual sound segments can be grouped into evolving sound units in order to capture language-specific sound laws more efficiently. We illustrate the usefulness of this enhanced representation of sound sequences in concrete examples and complement it by providing a small software library that allows scholars to convert their data from forms segmented into sound units to forms segmented into evolving sound units and vice versa.

In linguistics, it is difficult to clearly draw the boundaries between the sounds in individual words. What one linguist may analyze as two sounds, another linguist might analyze at just one sound. Since the segmentation of words into sounds is crucial for many analyses in linguistics and since no perfect solution can be found, we offer a new representation that allows scholars to analyze the sounds in a word in a more flexible way that conforms to general standards while at the same time giving linguists enough flexibility to advance individual analyses.

Inference of partial colexifications from multilingual wordlists.

The past years have seen a drastic rise in studies devoted to the investigation of colexification patterns in individual languages families in particular and the languages of the world in specific. Specifically computational studies have profited from the fact that colexification as a scientific construct is easy to operationalize, enabling scholars to infer colexification patterns for large collections of cross-linguistic data. Studies devoted to partial colexifications-colexification patterns that do not involve entire words, but rather various parts of words-, however, have been rarely conducted so far. This is not surprising, since partial colexifications are less easy to deal with in computational approaches and may easily suffer from all kinds of noise resulting from false positive matches. In order to address this problem, this study proposes new approaches to the handling of partial colexifications by (1) proposing new models with which partial colexification patterns can be represented, (2) developing new efficient methods and workflows which help to infer various types of partial colexification patterns from multilingual wordlists, and (3) illustrating how inferred patterns of partial colexifications can be computationally analyzed and interactively visualized.

Open Problems in Computational Historical Linguistics.

Problems constitute the starting point of all scientific research. The essay reflects on the different kinds of problems that scientists address in their research and discusses a list of 10 problems for the field of computational historical linguistics, that was proposed throughout 2019 in a series of blog posts (see http://phylonetworks.blogspot.com/). In contrast to problems identified in different contexts, these problems were considered to be solvable, but no solution could be proposed back then. By discussing the problems in the light of developments that have been made in the field during the past five years, a modified list is proposed that takes new insights into account but also finds that the majority of the problems has not yet been solved.

Lexical data for the historical comparison of Rgyalrongic languages.

As one of the most morphologically conservative branches of the Sino-Tibetan language family, most of the Rgyalrongic languages are still understudied and poorly understood, not to mention their vulnerable or endangered status. It is therefore important for available data of these languages to be made accessible. The lexical data sets the authors have assembled provide comparative word lists of 20 modern and medieval Rgyalrongic languages, consisting of word lists from fieldwork carried out by the first author and other colleagues as well as published word lists by other authors. In particular, data of the two Khroskyabs varieties were collected by the first author from 2011 to 2016. Cognate identification is based on the authors' expertise in Rgyalrong historical linguistics through application of the comparative method. We curated the data by conducting phonemic segmentation and partial cognate annotation. The data sets can be used by historical linguists interested in the etymology and the phylogeny of the languages in question, and they can use them to answer questions regarding individual word histories or the subgrouping of languages in this important branch of Sino-Tibetan.

Rgyalrongic languages are mainly spoken in Western Sichuan, China, though Tangut, an extinct mediaeval language, was attested in today's Ningxia province and its surrounding regions from 1036 to 1502 AD. They are the most difficult branch of languages to learn in the Sino-Tibetan family, as they exhibit complex word formation strategies such as inflection and derivation. Their word complexity points to their historical depth in the language group and their value in exploring Sino-Tibetan language history. The database considered in this article aims at gathering lexical information of Rgyalrongic languages, as a tool for research in the field of historical and evolutionary linguistics.

Untangling the evolution of body-part terminology in Pano: conservative versus innovative traits in body-part lexicalization.

Although language-family specific traits which do not find direct counterparts outside a given language family are usually ignored in quantitative phylogenetic studies, scholars have made ample use of them in qualitative investigations, revealing their potential for identifying language relationships. An example of such a family specific trait are body-part expressions in Pano languages, which are often lexicalized forms, composed of bound roots (also called body-part prefixes in the literature) and non-productive derivative morphemes (called here body-part formatives). We use various statistical methods to demonstrate that whereas body-part roots are generally conservative, body-part formatives exhibit diverse chronologies and are often the result of recent and parallel innovations. In line with this, the phylogenetic structure of body-part roots projects the major branches of the family, while formatives are highly non-tree-like. Beyond its contribution to the phylogenetic analysis of Pano languages, this study provides significative insights into the role of grammatical innovations for language classification, the origin of morphological complexity in the Amazon and the phylogenetic signal of specific grammatical traits in language families.

First steps towards the detection of contact layers in Bangime: a multi-disciplinary, computer-assisted approach.

Bangime is a language isolate, which has not been proven to be genealogically related to any other language family, spoken in Central-Eastern Mali. Its speakers, the Bangande, claim affiliation with the Dogon languages and speakers that surround them throughout a cliff range known as the Bandiagara Escarpment.  However, recent genetic research has shown that the Bangande are genetically distant from the Dogon and other groups. Furthermore, the Bangande people represent a genetic isolate.  Despite the geographic isolation of the Bangande people, evidence of language contact is apparent in the Bangime language. We find a plethora of shared vocabulary with neighboring Atlantic, Dogon, Mande, and Songhai language groups. To address the problem of when and whence this vocabulary emerged in the language, we use a computer-assisted, multidisciplinary approach to investigate layers of contact and inheritance in Bangime. We start from an automated comparison of lexical data from languages belonging to different language families in order to obtain a first account on potential loanword candidates in our sample. In a second step, we use specific interfaces to refine and correct the computational findings. The revised sample is then investigated quantitatively and qualitatively by focusing on vocabularies shared exclusively between specific languages. We couch our results within archeological and historical research from Central-Eastern Mali more generally and propose a scenario in which the Bangande formed part of the expansive Mali Empire that encompassed most of West Africa from the 13th to the 16th centuries. We consider our methods to represent a novel approach to the investigation of a language and population isolate from multiple perspectives using innovative computer-assisted technologies.

A comparative wordlist for the languages of The Gran Chaco, South America.

Home to more than twenty indigenous languages belonging to six linguistic families, the Gran Chaco has raised the interest of many linguists from different backgrounds. While some have focused on finding deeper genetic relations between different language groups, others have looked into similarities from the perspective of areal linguistics. In order to contribute to further research of areal and genetic features among these languages, we have compiled a comparative wordlist consisting of translational equivalents for 326 concepts - representing basic and ethnobiological vocabulary - for 26 language varieties. Since the data were standardized in various ways, they can be analyzed both quantitatively and qualitatively. In order to illustrate this in detail, we have carried out an initial computer-assisted analysis of parts of the data by searching for shared lexicosemantic patterns resulting from structural rather than direct borrowings.

Curating and extending data for language comparison in Concepticon and NoRaRe.

Language comparison requires user-friendly tools that facilitate the standardization of linguistic data. We present two resources built on the basis of a standardized cross-linguistic format and show how the data is curated and extended. The first resource, the Concepticon, is a reference catalog for standardized concepts from linguistic research. While curating the Concepticon, we found that a variety of studies in distinct research fields collected information on word properties. However, until recently, no resource existed that contained these data to enable the comparison of the different word properties across languages. This gap was filled by the Database of Norms, Ratings, and Relations (NoRaRe), which is an extension of the Concepticon. Here, we present the major release of both resources - Concepticon Version 3.0 and NoRaRe Version 1.0 - which represents an important step in our data development. We show that extending and adapting the data curation workflow in Concepticon to NoRaRe is useful for the standardization of cross-linguistic datasets. In addition, combining datasets from different research fields enables studies grounded in language comparison. Concepticon and NoRaRe include lexical data for various languages, tools for test-driven data curation, and the possibility for data reuse. The first major release of NoRaRe is also accompanied by a new web application that allows convenient access to the data.

From Text to Thought: How Analyzing Language Can Advance Psychological Science.

Humans have been using language for millennia but have only just begun to scratch the surface of what natural language can reveal about the mind. Here we propose that language offers a unique window into psychology. After briefly summarizing the legacy of language analyses in psychological science, we show how methodological advances have made these analyses more feasible and insightful than ever before. In particular, we describe how two forms of language analysis-natural-language processing and comparative linguistics-are contributing to how we understand topics as diverse as emotion, creativity, and religion and overcoming obstacles related to statistical power and culturally diverse samples. We summarize resources for learning both of these methods and highlight the best way to combine language analysis with more traditional psychological paradigms. Applying language analysis to large-scale and cross-cultural datasets promises to provide major breakthroughs in psychological science.

Networks uncover hidden lexical borrowing in Indo-European language evolution.

Language evolution is traditionally described in terms of family trees with ancestral languages splitting into descendent languages. However, it has long been recognized that language evolution also entails horizontal components, most commonly through lexical borrowing. For example, the English language was heavily influenced by Old Norse and Old French; eight per cent of its basic vocabulary is borrowed. Borrowing is a distinctly non-tree-like process--akin to horizontal gene transfer in genome evolution--that cannot be recovered by phylogenetic trees. Here, we infer the frequency of hidden borrowing among 2346 cognates (etymologically related words) of basic vocabulary distributed across 84 Indo-European languages. The dataset includes 124 (5%) known borrowings. Applying the uniformitarian principle to inventory dynamics in past and present basic vocabularies, we find that 1373 (61%) of the cognates have been affected by borrowing during their history. Our approach correctly identified 117 (94%) known borrowings. Reconstructed phylogenetic networks that capture both vertical and horizontal components of evolutionary history reveal that, on average, eight per cent of the words of basic vocabulary in each Indo-European language were involved in borrowing during evolution. Basic vocabulary is often assumed to be relatively resistant to borrowing. Our results indicate that the impact of borrowing is far more widespread than previously thought.

Automated identification of borrowings in multilingual wordlists.

Although lexical borrowing is an important aspect of language evolution, there have been few attempts to automate the identification of borrowings in lexical datasets. Moreover, none of the solutions which have been proposed so far identify borrowings across multiple languages. This study proposes a new method for the task and tests it on a newly compiled large comparative dataset of 48 South-East Asian languages from Southern China. The method yields very promising results, while it is conceptually straightforward and easy to apply. This makes the approach a perfect candidate for computer-assisted exploratory studies on lexical borrowing in contact areas.

The uses and abuses of tree thinking in cultural evolution.

Modern phylogenetic methods are increasingly being used to address questions about macro-level patterns in cultural evolution. These methods can illuminate the unobservable histories of cultural traits and identify the evolutionary drivers of trait change over time, but their application is not without pitfalls. Here, we outline the current scope of research in cultural tree thinking, highlighting a toolkit of best practices to navigate and avoid the pitfalls and 'abuses' associated with their application. We emphasize two principles that support the appropriate application of phylogenetic methodologies in cross-cultural research: researchers should (1) draw on multiple lines of evidence when deciding if and which types of phylogenetic methods and models are suitable for their cross-cultural data, and (2) carefully consider how different cultural traits might have different evolutionary histories across space and time. When used appropriately phylogenetic methods can provide powerful insights into the processes of evolutionary change that have shaped the broad patterns of human history. This article is part of the theme issue 'Foundations of cultural evolution'.

Evolutionary dynamics in the dispersal of sign languages.

The evolution of spoken languages has been studied since the mid-nineteenth century using traditional historical comparative methods and, more recently, computational phylogenetic methods. By contrast, evolutionary processes resulting in the diversity of contemporary sign languages (SLs) have received much less attention, and scholars have been largely unsuccessful in grouping SLs into monophyletic language families using traditional methods. To date, no published studies have attempted to use language data to infer relationships among SLs on a large scale. Here, we report the results of a phylogenetic analysis of 40 contemporary and 36 historical SL manual alphabets coded for morphological similarity. Our results support grouping SLs in the sample into six main European lineages, with three larger groups of Austrian, British and French origin, as well as three smaller groups centring around Russian, Spanish and Swedish. The British and Swedish lineages support current knowledge of relationships among SLs based on extra-linguistic historical sources. With respect to other lineages, our results diverge from current hypotheses by indicating (i) independent evolution of Austrian, French and Spanish from Spanish sources; (ii) an internal Danish subgroup within the Austrian lineage; and (iii) evolution of Russian from Austrian sources.

Using lexical language models to detect borrowings in monolingual wordlists.

Lexical borrowing, the transfer of words from one language to another, is one of the most frequent processes in language evolution. In order to detect borrowings, linguists make use of various strategies, combining evidence from various sources. Despite the increasing popularity of computational approaches in comparative linguistics, automated approaches to lexical borrowing detection are still in their infancy, disregarding many aspects of the evidence that is routinely considered by human experts. One example for this kind of evidence are phonological and phonotactic clues that are especially useful for the detection of recent borrowings that have not yet been adapted to the structure of their recipient languages. In this study, we test how these clues can be exploited in automated frameworks for borrowing detection. By modeling phonology and phonotactics with the support of Support Vector Machines, Markov models, and recurrent neural networks, we propose a framework for the supervised detection of borrowings in mono-lingual wordlists. Based on a substantially revised dataset in which lexical borrowings have been thoroughly annotated for 41 different languages from different families, featuring a large typological diversity, we use these models to conduct a series of experiments to investigate their performance in mono-lingual borrowing detection. While the general results appear largely unsatisfying at a first glance, further tests show that the performance of our models improves with increasing amounts of attested borrowings and in those cases where most borrowings were introduced by one donor language alone. Our results show that phonological and phonotactic clues derived from monolingual language data alone are often not sufficient to detect borrowings when using them in isolation. Based on our detailed findings, however, we express hope that they could prove to be useful in integrated approaches that take multi-lingual information into account.

The Database of Cross-Linguistic Colexifications, reproducible analysis of cross-linguistic polysemies.

Advances in computer-assisted linguistic research have been greatly influential in reshaping linguistic research. With the increasing availability of interconnected datasets created and curated by researchers, more and more interwoven questions can now be investigated. Such advances, however, are bringing high requirements in terms of rigorousness for preparing and curating datasets. Here we present CLICS, a Database of Cross-Linguistic Colexifications (CLICS). CLICS tackles interconnected interdisciplinary research questions about the colexification of words across semantic categories in the world's languages, and show-cases best practices for preparing data for cross-linguistic research. This is done by addressing shortcomings of an earlier version of the database, CLICS2, and by supplying an updated version with CLICS3, which massively increases the size and scope of the project. We provide tools and guidelines for this purpose and discuss insights resulting from organizing student tasks for database updates.