1 |
First steps towards the detection of contact layers in Bangime: a multi-disciplinary, computer-assisted approach
|
|
|
|
In: ISSN: 2732-5121 ; Open Research Europe ; https://hal.archives-ouvertes.fr/hal-03637688 ; Open Research Europe, F1000 Research Limited on behalf of the European Commission, 2022, 2, pp.10. ⟨10.12688/openreseurope.14339.1⟩ (2022)
|
|
BASE
|
|
Show details
|
|
2 |
A New Framework for Fast Automated Phonological Reconstruction Using Trimmed Alignments and Sound Correspondence Patterns ...
|
|
|
|
BASE
|
|
Show details
|
|
3 |
Chances and Challenges for Quantitative Approaches in Chinese Historical Phonology ...
|
|
|
|
BASE
|
|
Show details
|
|
4 |
Computational Approaches to Historical Language Comparison ...
|
|
|
|
BASE
|
|
Show details
|
|
5 |
Modeling word trees in historical linguistics. Preliminary ideas for the reconciliation of word trees and language trees ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
First steps towards the detection of contact layers in Bangime: a multi-disciplinary, computer-assisted approach
|
|
|
|
In: ISSN: 2732-5121 ; Open Research Europe ; https://hal.archives-ouvertes.fr/hal-03637688 ; Open Research Europe, F1000 Research Limited on behalf of the European Commission, 2022, 2, pp.10. ⟨10.12688/openreseurope.14339.1⟩ (2022)
|
|
BASE
|
|
Show details
|
|
8 |
Computer-assisted approaches to historical language comparison ...
|
|
|
|
BASE
|
|
Show details
|
|
9 |
Correcting a Bias in TIGER Rates Resulting from High Amounts of Invariant and Singleton Cognate Sets ...
|
|
|
|
Abstract:
In a recent issue of the Journal of Language Evolution, Syrjänen et al. (2021) investigate the suitability of computing Cummins and McInerney’s (2011) TIGER rates for estimating the tree-likeness of linguistic datasets compiled for phylogenetic reconstruction. The authors test the TIGER rates on a diverse sample of simulated data, which by and large confirms the usefulness of TIGER rates as an analytic tool for investigating linguistic data, but they test them only on one real-world dataset of Uralic languages which turns out to behave quite differently from the simulated data. When testing the TIGER rates on additional datasets, I detected a bias in the computation which leads to an unnatural increase in those cases where a dataset contains many characters with invariant or singleton states. To overcome this problem, I suggest a modified variant of TIGER rates, which is provided in the form of a freely available Python package. Testing the modified TIGER scores on the simulated data of Syrjänen et al. shows ...
|
|
Keyword:
Historical linguistics
|
|
URL: https://hcommons.org/deposits/item/hc:43565/ https://dx.doi.org/10.17613/0n1n-3352
|
|
BASE
|
|
Hide details
|
|
12 |
Prediction experiment for missing words in Kho-Bwa language data ...
|
|
|
|
BASE
|
|
Show details
|
|
13 |
CLDF Dataset accompanying Greenhill et al.'s "Origin of Uto-Aztecan" from 2021 ...
|
|
|
|
BASE
|
|
Show details
|
|
18 |
CLDF Dataset accompanying Greenhill et al.'s "Origin of Uto-Aztecan" from 2021 ...
|
|
|
|
BASE
|
|
Show details
|
|
19 |
Annotating Cognates in Phylogenetic Studies of South-East Asian Languages ...
|
|
|
|
BASE
|
|
Show details
|
|
20 |
Computer-assisted approaches to historical language comparison
|
|
|
|
BASE
|
|
Show details
|
|
|
|