We present a fully automated workflow for phylogenetic reconstruction on large datasets, consisting of two novel methods, one for fast detection of cognates and one for fast Bayesian phylogenetic inference. Our results show that the methods take less than a few minutes to process language families that have so far required large amounts of time…[Read more]

We present a fully automated workflow for phylogenetic reconstruction on large datasets, consisting of two novel methods, one for fast detection of cognates and one for fast Bayesian phylogenetic inference. Our results show that the methods take less than a few minutes to process language families that have so far required large amounts of time…[Read more]

We present a fully automated workflow for phylogenetic reconstruction on large datasets, consisting of two novel methods, one for fast detection of cognates and one for fast Bayesian phylogenetic inference. Our results show that the methods take less than a few minutes to process language families that have so far required large amounts of time…[Read more]

We present a fully automated workflow for phylogenetic reconstruction on large datasets, consisting of two novel methods, one for fast detection of cognates and one for fast Bayesian phylogenetic inference. Our results show that the methods take less than a few minutes to process language families that have so far required large amounts of time…[Read more]

Blog post, published with the blog “History and Philosophy of the Language Sciences”. Here shared in form of a paper draft. Please cite as:

List, Johann-Mattis. 2018. Towards a history of concept list compilation in historical linguistics. History and Philosophy of the Language Sciences. http://hiphilangsci.net/2018/10/31/concept-list-compilation/

Blog post, published with the blog “History and Philosophy of the Language Sciences”. Here shared in form of a paper draft. Please cite as:

List, Johann-Mattis. 2018. Towards a history of concept list compilation in historical linguistics. History and Philosophy of the Language Sciences. http://hiphilangsci.net/2018/10/31/concept-list-compilation/

Blog post, published with the blog “History and Philosophy of the Language Sciences”. Here shared in form of a paper draft. Please cite as:

List, Johann-Mattis. 2018. Towards a history of concept list compilation in historical linguistics. History and Philosophy of the Language Sciences. http://hiphilangsci.net/2018/10/31/concept-list-compilation/

The Database of Cross-Linguistic Colexifications (CLICS), has established a computer-assisted framework for the interactive representation of cross-linguistic colexification patterns. In its current form, it has proven to be a useful tool for various kinds of investigation into cross-linguistic semantic associations, ranging from studies on…[Read more]

The Database of Cross-Linguistic Colexifications (CLICS), has established a computer-assisted framework for the interactive representation of cross-linguistic colexification patterns. In its current form, it has proven to be a useful tool for various kinds of investigation into cross-linguistic semantic associations, ranging from studies on…[Read more]

The Database of Cross-Linguistic Colexifications (CLICS), has established a computer-assisted framework for the interactive representation of cross-linguistic colexification patterns. In its current form, it has proven to be a useful tool for various kinds of investigation into cross-linguistic semantic associations, ranging from studies on…[Read more]

We evaluate the performance of state-of-the-art algorithms for automatic cognate detection by comparing how useful automatically
inferred cognates are for the task of phylogenetic inference compared to classical manually
annotated cognate sets. Our findings suggest
that phylogenies inferred from automated cog-
nate sets come close to…[Read more]

We evaluate the performance of state-of-the-art algorithms for automatic cognate detection by comparing how useful automatically
inferred cognates are for the task of phylogenetic inference compared to classical manually
annotated cognate sets. Our findings suggest
that phylogenies inferred from automated cog-
nate sets come close to…[Read more]

Current efforts in computational historical linguistics are predominantly concerned
with phylogenetic inference. Methods for ancestral state reconstruction have only
been applied sporadically. In contrast to phylogenetic algorithms, automatic reconstruction methods presuppose phylogenetic information in order to explain what has
evolved when…[Read more]

Current efforts in computational historical linguistics are predominantly concerned
with phylogenetic inference. Methods for ancestral state reconstruction have only
been applied sporadically. In contrast to phylogenetic algorithms, automatic reconstruction methods presuppose phylogenetic information in order to explain what has
evolved when…[Read more]

Current efforts in computational historical linguistics are predominantly concerned
with phylogenetic inference. Methods for ancestral state reconstruction have only
been applied sporadically. In contrast to phylogenetic algorithms, automatic reconstruction methods presuppose phylogenetic information in order to explain what has
evolved when…[Read more]

The discipline of Historical Chinese Phonology has made great progress during the last thirty years.
Thanks to these improvements we have now a much clearer picture of the history of the Chinese language and the development of the Chinese writing system. Since Historical Chinese Phonology is an
inherently data-driven discipline, it is, however,…[Read more]

With increasing amounts of digitally available data from all over the world, manual annotation of cognates in multi-lingual word lists becomes more and more time-consuming in historical linguistics. Using available software packages to pre-process the data prior to manual analysis can drastically speed-up the process of cognate detection.…[Read more]