Towards automated language classification: A clustering approach

Kapitel in diesem Buch

1. Frontmatter i
2. Preface v
3. Contents vii
4. Introduction
5. The why and how of measuring linguistic differences 3
6. Case studies
7. Contrasting linguistics and archaeology in the matrix model: GIS and cluster analysis of the Arawakan languages 29
8. Predicting language-learning difficulty 57
9. How aberrant are divergent Indo-European subgroups? 83
10. Measuring socially motivated pronunciation differences 107
11. Distance-based phylogenetic inference algorithms in the subgrouping of Dravidian languages 141
12. Carving Tibeto-Kanauri by its joints: Using basic vocabulary lists for genetic grouping of languages 175
13. The effect of linguistic distance across Indo-European mother tongues on learning Dutch as a second language 199
14. Using semantically restricted word-lists to investigate relationships among Athapaskan languages 231
15. Languages with longer words have more lexical change 249
16. Methods and tools
17. The Intercontinental Dictionary Series – a rich and principled database for language comparison 285
18. Towards automated language classification: A clustering approach 303
19. Dependency-sensitive typological distance 329
20. Degrees of semantic control in measuring aggregated lexical distances 353
21. Word similarity, cognation, and translational equivalence 375
22. Comparing linguistic systems of categorisation 387
23. Black box approaches to genealogical classification and their shortcomings 429
24. Semantic typologies by means of network analysis of bilingual dictionaries 447
25. Measuring morphosemantic language distance in parallel texts 475
26. Information-theoretic modeling of etymological sound change 507
27. Index 533