Chinese Restaurant Process for cognate clustering: A threshold free approach
This work addresses the need for efficient and threshold-free methods in historical linguistics for clustering cognates across languages, though it appears incremental as it matches existing performance.
The paper tackles the problem of cognate clustering by introducing a threshold-free approach based on the Chinese Restaurant Process, which yields results similar to the linguistically motivated LexStat system and is fast and applicable to any language family.
In this paper, we introduce a threshold free approach, motivated from Chinese Restaurant Process, for the purpose of cognate clustering. We show that our approach yields similar results to a linguistically motivated cognate clustering system known as LexStat. Our Chinese Restaurant Process system is fast and does not require any threshold and can be applied to any language family of the world.