Multiple sequence alignments in linguistics

2018

Preprint

Johann-Mattis List 2018Sound correspondence patterns play a crucial role for linguistic reconstruction. Linguists use them to prove language relationship, to reconstruct proto-forms, and for classical phylogenetic reconstruction based on shared innovations.Cognate words which fail to conform with expected patterns can further point to various kinds of exceptions in sound change, such as analogy or assimilation of frequent words. Here we present an automatic method for the inference of sound correspondence patterns across multiple languages based on a network approach. The core idea is to represent all columns in aligned cognate sets as nodes in a network with edges representing the degree of compatibility between the nodes. The task of inferring all compatible correspondence sets can then be handled as the well-known minimum clique cover problem in graph theory, which essentially seeks to split the graph into the smallest number of cliques in which each node is represented by exactly one clique. The resulting partitions represent all correspondence patterns which can be inferred for a given dataset. By excluding those patterns which occur in only a few cognate sets, the core of regularly recurring sound correspondences can be inferred. Based on this idea, the paper presents a method for automatic correspondence pattern recognition, which is implemented as part of a Python library which supplements the paper. To illustrate the usefulness of the method, we present how the inferred patterns can be used to predict words that have not been observed before.

Section: Implementation Input Format and Output Formatmentioning

confidence: 99%

“…With increasing amounts of data, however, the methods, which are largely manually applied, reach their practical limits. As a result, scholars are now increasingly trying to automatize different aspects of the classical comparative methods (Kondrak, 2000;Prokić, Wieling, and Nerbonne, 2009;List, 2014).…”

Section: Introductionmentioning

confidence: 99%

Automatic Inference of Sound Correspondence Patterns Across Multiple Languages

2018

Preprint

“…The past two decades have seen a drastic increase of quantitative applications in historical linguistics and linguistic typology, witnessed by multiple articles dealing with the automation of formerly exclusively manual tasks, such as phylogenetic reconstruction (Gray & Atkinson, ; Holman et al, ), word comparison (Kondrak, ; List, Greenhill, & Gray, ; Prokić, Wieling, & Nerbonne, ), semantic change (Dellert, ; Eger & Mehle, ; Steiner, Stadler, & Cysouw, ), and regular sound correspondences (Brown, Holman, & Wichmann, ; Kondrak, ; List, ). The quantitative turn was specifically favored by the compilation of large databases, offering cross‐linguistic accounts on typological structures (Dryer & Haspelmath, ; Polyakov & Solovyev, ), lexical cognates (Greenhill, Blust, & Gray, ; Matisoff, ; Starostin, ), lexical data in general (Dellert & Jäger, ; Kaiping & Klamer, ), phoneme inventories (Maddieson, Flavier, Marsico, Coupé, & Pellegrino, ; Moran, McCloy, & Wright, ), and polysemies (List et al, ).…”

Section: Introductionmentioning

confidence: 99%

Automated methods for the investigation of language contact, with a focus on lexical borrowing

Language and Linguist. Compass

2019

While language contact has so far been predominantly studied on the basis of detailed case studies, the emergence of methods for phylogenetic reconstruction and automated word comparison—as a result of the recent quantitative turn in historical linguistics—has also resulted in new proposals to study language contact situations by means of automated approaches. This study provides a concise introduction to the most important approaches, which have been proposed in the past, presenting methods that use (A) phylogenetic networks to detect reticulation events during language history, (B) sequence comparison methods in order to identify borrowings in multilingual datasets, and (C) arguments for the borrowability of shared traits to decide if traits have been borrowed or inherited. While the overview focuses on approaches dealing with lexical borrowing, questions of general contact inference will also be discussed where applicable.

“…To detect regularly recurring sound correspondences linguists usually rely on alignment analyses (Prokić et al 2009;List 2014). Alignments are a formal way to compare sequences.…”

Section: Using Alignments For Sound-correspondence Annotationmentioning

confidence: 99%

Challenges of annotation and analysis in computer-assisted language comparison: A case study on Burmish languages

Hill

Yearbook of the Poznan Linguistic Meeting

2017

The use of computational methods in comparative linguistics is growing in popularity. The increasing deployment of such methods draws into focus those areas in which they remain inadequate as well as those areas where classical approaches to language comparison are untransparent and inconsistent. In this paper we illustrate specific challenges which both computational and classical approaches encounter when studying South-East Asian languages. With the help of data from the Burmish language family we point to the challenges resulting from missing annotation standards and insufficient methods for analysis and we illustrate how to tackle these problems within a computer-assisted framework in which computational approaches are used to pre-analyse the data while linguists attend to the detailed analyses.