Validating Dialect Comparison Methods

Nerbonne, John; Kleiweg, Peter

doi:10.1007/978-3-642-55991-4_48

Cited by 28 publications

(22 citation statements)

References 3 publications

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“…The essential calculations are as follows: Figure 1: Dialect distance as a logarithmic function of geographic distance, from Heeringa & Nerbonne (2002). Note that the linguistic distance to more remote varieties appears to level off to a fairly flat level, suggesting that such distant points no longer reflect distance in linguistic dissimilarity as reliably.…”

Section: Geographic Coherencementioning

confidence: 99%

“…Heeringa, Nerbonne & Kleiweg (2002) acknowledged that this technique suffers in its reliance on the exploratory technique of clustering, and Heeringa (2004) added to this the note that the data points ignored (in the step of restricting one's attention to elements for which there is consensus) often are classified in ways which indicate problems. In such cases there may be a dispute about whether a borderline data point belongs to A or B, but classifying it as C is a clear error.…”

Section: Lexical Differencesmentioning

confidence: 99%

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Toward a dialectological yardstick*

Nerbonne

Kleiweg

2007

Journal of Quantitative Linguistics

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Dialectometry measures the differences between dialects in ways which may involve many independently varying parameters which must be specified in combination in order to arrive at measures of difference. The existence of many parameters of measurement and possible interaction introduces the problem of how to choose parameter values and combinations of them intelligently. This paper proceeds from the assumption that dialectology proper must reveal geographic coherence in language variation in order to propose a yardstick with which to compare measurements made using various parameter settings, and it presents some results of its application.

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Section: Geographic Coherencementioning

confidence: 99%

Section: Lexical Differencesmentioning

confidence: 99%

Toward a dialectological yardstick*

Nerbonne

Kleiweg

2007

Journal of Quantitative Linguistics

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“…[Cronbach's alpha has been suggested as a way to validate word-based methods for comparing dialects (18), and the argument carries over to cross-linguistic data. It ranges from 0 to 1, where 0 means "totally inconsistent" and 1 means "fully consistent."]…”

Section: Significancementioning

confidence: 99%

Support for linguistic macrofamilies from weighted sequence alignment

Jäger

2015

Proc. Natl. Acad. Sci. U.S.A.

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Computational phylogenetics is in the process of revolutionizing historical linguistics. Recent applications have shed new light on controversial issues, such as the location and time depth of language families and the dynamics of their spread. So far, these approaches have been limited to single-language families because they rely on a large body of expert cognacy judgments or grammatical classifications, which is currently unavailable for most language families. The present study pursues a different approach. Starting from raw phonetic transcription of core vocabulary items from very diverse languages, it applies weighted string alignment to track both phonetic and lexical change. Applied to a collection of ∼1,000 Eurasian languages and dialects, this method, combined with phylogenetic inference, leads to a classification in excellent agreement with established findings of historical linguistics. Furthermore, it provides strong statistical support for several putative macrofamilies contested in current historical linguistics. In particular, there is a solid signal for the Nostratic/Eurasiatic macrofamily. The scope of this method, according to a near-consensus in the field, is intrinsically limited to a time depth of ∼10,000 y, however. Over the past century, there have been an abundance of proposals for macrofamilies going back further in time. Few of these proposals are currently backed up by evidence as strong as is required by the professional standards of historical comparative linguistic research. These professional standards demand reconstruction of a substantial portion of the protolanguage's vocabulary and grammar plus the historic processes leading to its attested descendants, which are vetted and approved by the scholarly community via peer review. So far, Afro-Asiatic is arguably the only macrofamily coming close to meeting these criteria; all other proposals along those lines are currently hypotheses at best, with varying degree of empirical justification. Perhaps the most intensely discussed such proposal concerns the Eurasiatic macrofamily (2, 3), comprising a large portion of uncontroversial families from Eurasia. A recent statistical study by Pagel et al. (4) estimated its time depth at 14,450 y.The study by Pagel et al. (4), as well as other recent applications of phylogenetic methods to historical linguistics (5-7) (for critical assessments see refs. 8 and 9), bases its inference on expert cognacy judgments. These judgments are largely consensual within accepted language families but necessarily controversial beyond that limit. Therefore, the findings of Pagel et al. (4) have sparked a fair amount of critical discussion among historical linguists (e.g., 10). Grammatical classifications (11,12) are an alternative to cognacy data; they are also available only on a relatively small sample of languages in sufficient detail at this time.To sidestep this issue, the present investigation pursues a purely data-oriented approach not reliant on expert judgments. It is based on data from the Automated ...

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“…Before generating a linguistic distance matrix, Cronbach's alpha was used to measure the internal consistency of the linguistic variables in the regional linguistic data matrix (Nerbonne and Heeringa, 1997;Heeringa et al, 2002;Heeringa, 2004;Nerbonne, 2008;Szmrecsanyi, 2008;Spruit et al, 2009). Cronbach's alpha was originally developed to assess if a set of items in a psychometric test measure the same underlying construct based on the scores on the test items for a sample of test takers (Cronbach, 1951).…”

Section: Cronbach's Alphamentioning

confidence: 99%

A comparison of statistical methods for the aggregation of regional linguistic variation

Grieve¹

2014

Aggregating Dialectology, Typology, and Register Analysis

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This paper compares two statistical approaches to the analysis of aggregated regional linguistic variation. In the standard approach to dialectometry, common patterns of regional variation are identified by analyzing the distance between a set of locations based on the values of a set of linguistic variables using statistics such as multivariate scaling.Alternatively, in a multivariate spatial analysis, common patterns of regional variation are identified by using a factor analysis to analyze correlations between linguistic variables that are first smoothed using a local spatial autocorrelation analysis that identifies underlying spatial patterns in the values of each variable. To compare these approaches, both methods are used to analyze the acoustic vowel data from the Atlas of North American English. It is concluded that the multivariate spatial analysis identifies clearer and more detailed patterns of aggregated regional linguistic variation than the standard approach to dialectometry.

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Validating Dialect Comparison Methods

Cited by 28 publications

References 3 publications

Toward a dialectological yardstick*

Toward a dialectological yardstick*

Support for linguistic macrofamilies from weighted sequence alignment

A comparison of statistical methods for the aggregation of regional linguistic variation

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