This paper describes a computerized alternative to glottochronology for estimating elapsed time since parent languages diverged into daughter languages. The method, developed by the Automated Similarity Judgment Program (ASJP) consortium, is different from glottochronology in four major respects: (1) it is automated and thus is more objective, (2) it applies a uniform analytical approach to a single database of worldwide languages, (3) it is based on lexical similarity as determined from Levenshtein (edit) distances rather than on cognate percentages, and (4) it provides a formula for date calculation that mathematically recognizes the lexical heterogeneity of individual languages, including parent languages just before their breakup into daughter languages. Automated judgments of lexical similarity for groups of related languages are calibrated with historical, epigraphic, and archaeological divergence dates for 52 language groups. The discrepancies between estimated and calibration dates are found to be on average 29% as large as the estimated dates themselves, a figure that does not differ significantly among language families. As a resource for further research that may require dates of known level of accuracy, we offer a list of ASJP time depths for nearly all the world's recognized language families and for many subfamilies. The greater the degree of linguistic differentiation within a stock, the greater is the period of time that must be assumed for the development of such differentiations.

The ASJP project aims at establishing relationships between languages on the basis of the Swadesh word list. For this purpose, lists have been collected and phonologically transcribed for almost 3,500 languages. Using a method based on the algorithm proposed by Levenshtein (1966), a custom-made computer program calculates the distances between all pairs of languages in the database. Standard software is used to express the relationships between languages graphically. The current article compares the results of our lexiconbased approach with the results of a similar exercise that takes the typological variables contained in the WALS database as a point of departure. We establish that the latter approach leads to even better results than the lexicon-based one. The best result in terms of correspondence with some well-established genetic and areal classifications, however, is attained when the lexical and typological methods are combined, especially if we select both the most stable Swadesh items and the most stable WALS variables.

No abstract

Lexical stress is realised similarly in English, German, and Dutch. On a suprasegmental level, stressed syllables tend to be longer and more acoustically salient than unstressed syllables; segmentally, vowels in unstressed syllables are often reduced. The frequency of unreduced unstressed syllables (where only the suprasegmental cues indicate lack of stress) however, differs across the languages. The present studies test whether listener behaviour is affected by these vocabulary differences, by investigating German listeners' use of suprasegmental cues to lexical stress in German and English word recognition. In a forced-choice identification task, German listeners correctly assigned single-syllable fragments (e.g., Kon-) to one of two words differing in stress (KONto, konZEPT). Thus, German listeners can exploit suprasegmental information for identifying words. German listeners also performed above chance in a similar task in English (with, e.g., DIver, diVERT), i.e., their sensitivity to these cues also transferred to a nonnative language. An English listener group, in contrast, failed in the English fragment task. These findings mirror vocabulary patterns: German has more words with unreduced unstressed syllables than English does.

A field-based ultrasound and acoustic study of Iwaidja, an endangered Australian Aboriginal language, investigates the phonetic identity of nonnasal velar consonants in intervocalic position, where past work has proposed a [+continuant] vs. [−continuant] phonemic contrast. We analyze the putative contrast within a continuous phonetic space, defined by both acoustic and articulatory parameters, and find gradient variation: from more consonantal realizations, such as [ɰ], to more vocalic realizations, such as [a]. The distribution of realizations across lexical items and speakers does not support the proposed phonemic contrast. This case illustrates how lenition that is both phonetically gradient and variable across speakers and words can give the illusion of a contextually restricted phonemic contrast.*