Expanding the PAn consonant inventory

This paper provides evidence for three Proto Austronesian (PAn) phonemes that are preserved in several distinct languages and subgroups. These include distinctions between *p and *f, *l and *ɭ, and *k and *g. In addition, we assert that there is expanded evidence in Malayo-Polynesian for two currently recognized phonemes: *ʈ (PAn *C) and *c; evidence for the former has been restricted until now to the Formosan languages, and for the latter to a small group of languages in western Indonesia. These contrasts can be found in Nias (one of the Barrier Island languages off the northwest coast of Sumatra), Dohoi (a Northwest Barito subgroup of Borneo), the Western Central Malayo-Polynesian languages of Bimanese, Hawu, Dhao, Western Oceanic, and more sparsely in languages of North Sarawak, the Philippines, and Sumba. The findings presented in this paper highlight the importance of the above languages and subgroups for PAn reconstruction, and the new phonemes presented here are placed within the context of a wider PAn inventory which includes a total of seven places of articulation.Australian National Universit

A Phonological Reconstruction of Proto-Hlai

This dissertation presents a reconstruction of the phoneme inventory of Proto-Hlai, based on data from twelve Hlai languages spoken on Hainan, China. A classification of the Hlai languages is given with the innovations upon which it based, followed by a discussion of contact relationships and a discussion of reconstruction methodology. The inventory of Proto-Hlai initials is reconstructed, and original sesquisyllabic forms are shown to be necessary to account for the reflexes between the daughter languages; the initial inventory is also marked by the presence of aspiration on most consonants in word-initial position. This is followed by the reconstruction of the rime inventory, an outstanding features of which is two laryngeal components which are argued to have been the precursors to two of the synchronic tone categories in the daughter languages, and which conditioned segmental variation in most of the daughter languages. A comparison is made between Proto-Hlai, Proto-Be, and Proto-Southwest Tai, and a preliminary reconstruction of Proto-Southern Kra-Dai (the immediate ancestor of Proto-Hlai) is performed. When this reconstruction is compared with that of Proto-Hlai, it is shown that several important sound changes occurred in Pre-Hlai, including intervocalic obstruent lenition, vocalic transfer, aspiration of word-initial consonants, and peripheral vowel raising. The language Jiamao is examined in detail, and it is argued that Jiamao is a non-Hlai language which has been in close contact with Hlai since the Pre-Hlai period. An examination of the correspondences between Jiamao and Hlai reveal at least two layers of Hlai loanwords in Jiamao, and evidence Jiamao was originally very different from Hlai structurally. Finally, the Proto-Hlai lexicon is compared with those of other Southeast Asian language phyla, and it is shown that Hlai retains evidence of shared lexicon (via either a genetic or contact relationship) with Sino-Tibetan, Mon-Khmer, Hmong-Mien, and Austronesian, the last of which is particularly striking. The dissertation concludes with a summary of findings, empirical and theoretical contributions, and suggestions for future research

A Hypothesis on the Origin of Preglottalized Sonorants in Kra-Dai

Non UBCUnreviewedPostdoctora

Appendix to A Phonological Reconstruction of Proto-Hlai

<p>Appendix to A Phonological Reconstruction of Proto-Hlai</p

alineR: an R Package for Optimizing Feature-Weighted Alignments and Linguistic Distances

Linguistic distance measurements are commonly used in anthropology and biology when quantitative and statistical comparisons between words are needed. This is common, for example, when analyzing linguistic and genetic data. Such comparisons can provide insight into historical population patterns and evolutionary processes. However, the most commonly used linguistic distances are derived from edit distances, which do not weight phonetic features that may, for example, represent smaller-scale patterns in linguistic evolution. Thus, computational methods for calculating feature-weighted linguistic distances are needed for linguistic, biological, and evolutionary applications; additionally, the linguistic distances presented here are generic and may have broader applications in fields such as text mining and search, as well as applications in psycholinguistics and morphology. To facilitate this research, we are making available an open-source R software package that performs feature-weighted linguistic distance calculations. The package also includes a supervised learning methodology that uses a genetic algorithm and manually determined alignments to estimate 13 linguistic parameters including feature weights and a skip penalty. Here we present the package and use it to demonstrate the supervised learning methodology by estimating the optimal linguistic parameters for both simulated data and for a sample of Austronesian languages. Our results show that the methodology can estimate these parameters for both simulated and real language data, that optimizing feature weights improves alignment accuracy by approximately 29%, and that optimization significantly affects the resulting distance measurements. Availability: alineR is available on CRAN.National Science Foundation [SBS-1030031]; University of MarylandOpen Access JournalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Tables: 10

1 Historical relationships among languages are used as a proxy for social history in many non-linguistic settings, including the fields of cultural and molecular anthropology. Linguists have traditionally assembled this information using the standard comparative method. While providing extremely nuanced linguistic information, this approach is time consuming and labor intensive. Conversely, computational approaches are appreciably quicker, but can potentially introduce significant error. Furthermore, current methods often use cognate sets that were themselves coded by historical linguists, thus reducing the benefit of computational approaches. Here we develop a method, based on the ALINE distance, to extract feature-sensitive relationships from paired glosses, datasets that require minimal contribution from trained linguists beyond transcription from primary sources. We validate our results by comparison with data generated independently via the comparative method, and quantify error rates using consistency indices. To showcase our method’s utility and to demonstrate its robustness at local and regional scales, we apply it to two language datasets from eastern Indonesia. As linguistic datasets proliferate, scalable computational methods that mimic historical linguistic reconstruction will become increasingly necessary