Morphological Typology in BPE Subword Productivity and Language Modeling

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autor principal: Parra, Iñigo
Formato: Preprint
Publicado: 2024
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866909373314367488
author Parra, Iñigo
author_facet Parra, Iñigo
contents This study investigates the impact of morphological typology on tokenization and language modeling performance. We focus on languages with synthetic and analytical morphological structures and examine their productivity when tokenized using the byte-pair encoding (BPE) algorithm. We compare the performance of models trained with similar amounts of data in different languages. Our experiments reveal that languages with synthetic features exhibit greater subword regularity and productivity with BPE tokenization and achieve better results in language modeling tasks. We also observe that the typological continuum from linguistic theory is reflected in several experiments. These findings suggest a correlation between morphological typology and BPE tokenization efficiency.
format Preprint
id arxiv_https___arxiv_org_abs_2410_23656
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Morphological Typology in BPE Subword Productivity and Language Modeling
Parra, Iñigo
Computation and Language
This study investigates the impact of morphological typology on tokenization and language modeling performance. We focus on languages with synthetic and analytical morphological structures and examine their productivity when tokenized using the byte-pair encoding (BPE) algorithm. We compare the performance of models trained with similar amounts of data in different languages. Our experiments reveal that languages with synthetic features exhibit greater subword regularity and productivity with BPE tokenization and achieve better results in language modeling tasks. We also observe that the typological continuum from linguistic theory is reflected in several experiments. These findings suggest a correlation between morphological typology and BPE tokenization efficiency.
title Morphological Typology in BPE Subword Productivity and Language Modeling
topic Computation and Language
url https://arxiv.org/abs/2410.23656