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University of Illinois at Urbana-Champaign

Improving neural language models on low-resource creole languages

Abstract

dc:description

When using neural models for NLP tasks, like language modelling, it is difficult to utilize a language with little data, also known as a low-resource language. Creole languages are frequently low-resource and as such it is difficult to train neural language models for them well. Creole languages are a special type of language that is widely thought of as having multiple parents and thus receiving a mix of evolutionary traits from all of them. One of a creole language’s parents is known as the lexifier, which gives the creole its lexicon, and the other parents are known as substrates, which possibly are thought to give the creole language its morphology and syntax. Creole languages are most lexically similar to their lexifier and most syntactically similar to otherwise unrelated creole languages. High lexical similarity to the lexifier is unsurprising because by definition lexifiers provide a creole’s lexicon, but high syntactic similarity to the other unrelated creole languages is not obvious and is explored in detail. We can use this information about creole languages’ unique genesis and typology to decrease the perplexity of neural language models on low-resource creole languages. We discovered that syntactically similar languages (especially other creole languages) can successfully transfer learned features during pretraining from a high-resource language to a low-resource creole language through a method called neural stacking. A method that normalized the vocabulary of a creole language to its lexifier also lowered perplexities of creole-language neural models.

Degree

thesis:*
Name thesis:degree_name
M.S.
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Computer Science
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Schieferstein, Sarah
Contributors dc:contributor
  • Hockenmaier, Julia

Subjects

dc:subject × 6

Rights

dc:rights
Statement dc:rights
  • Copyright 2018 Sarah Schieferstein
Language dc:language
en

Identifiers

dc:identifier.*
Handle dc:identifier
http://hdl.handle.net/2142/102512
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/102512

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Schieferstein, Sarah. Improving neural language models on low-resource creole languages. Thesis thesis, University of Illinois at Urbana-Champaign, 2019. http://hdl.handle.net/2142/102512