Consonant (De)gradation in Ingrian?

<p>This paper will present a dual method toward data enrichment for low-resource languages. Using Yoyodyne -- a Fairseq-inspired neural library for small-vocabulary sequence-to-sequence generation -- a morphological generation task was tested across labeled data encompassing multiple stages of enrichment for the low-resource language Ingrian. Due to limitations in the available data for Ingrian, weighted finite-state transducers (WFSTs) were used to generate an expanded vocabulary via HFST's toolkit for Uralic languages, and GiellaLT, a source for FST-driven lexica for low-resource languages. Further stages of experimentation used labeled data from related, higher-resource languages (Finnish, Estonian) to encourage cross-lingual transfer in the interest of paradigm completion.</p>

Name thesis:degree_name

Master of Arts

Level thesis:degree_level

Master

Discipline thesis:degree_discipline

Linguistics

Grantor

The Graduate School and University Center of The City University of New York

Year dc:date.available

2024

Author dc:creator

• Harrison, Andrea M.

Advisor dc:contributor.advisor

• Kyle Gorman

• Computational Linguistics
• Low-resource languages
• Finno-Ugric languages
• Uralic languages
• Ingrian
• Computational morphology
• Morphophonology

Repository record dc:identifier

https://academicworks.cuny.edu/gc_etds/5677

OAI identifier oai:identifier

oai:academicworks.cuny.edu:gc_etds-6805