Work

Vorm: Translations and a constrained hypothesis space support unsupervised morphological segmentation across languages

Year: 2025

Type: conference-paper

Abstract: This paper introduces VORM, an unsupervised morphological segmentation system, leveraging translation data to infer highly accurate morphological transformations, including lessfrequently modeled processes such as infixation and reduplication.The system is evaluated on standard benchmark data and a novel, typologically diverse, dataset of 37 languages.Model performance is competitive and sometimes superior on canonical segmentation, but more limited on surface segmentation.

Source: Conference on Computational Natural Language Learning

DOI: 10.18653/v1/2025.conll-1.39

Author: Barend Beekhuizen

Institution: University of Toronto

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4412888995

FWCI: 0.991

Cites:

Cited by: 1

Related to: 10