CLJul 27, 2016
Synthetic Language Generation and Model Validation in BEAST2
arXiv:1607.07931v11 citations
Originality Synthesis-oriented
AI Analysis
This work addresses validation challenges for computational linguistic models, though it is incremental as it builds on an existing framework.
The authors extended the BEAST2 phylogenetic framework to generate synthetic languages under multiple models, and used this plugin to test how word borrowing affects inference in two common phylolinguistic models.
Generating synthetic languages aids in the testing and validation of future computational linguistic models and methods. This thesis extends the BEAST2 phylogenetic framework to add linguistic sequence generation under multiple models. The new plugin is then used to test the effects of the phenomena of word borrowing on the inference process under two widely used phylolinguistic models.