Adaptor Grammars for the Linguist: Word Segmentation Experiments for Very Low-Resource Languages - Archive ouverte HAL Access content directly
Conference Papers Year :

Adaptor Grammars for the Linguist: Word Segmentation Experiments for Very Low-Resource Languages

(1) , (2) , (1) , (3) , (1) , (1) , (3)
1
2
3

Abstract

Computational Language Documentation attempts to make the most recent research in speech and language technologies available to linguists working on language preservation and documentation. In this paper, we pursue two main goals along these lines. The first is to improve upon a strong baseline for the unsupervised word discovery task on two very low-resource Bantu languages, taking advantage of the expertise of linguists on these particular languages. The second consists in exploring the Adaptor Grammar framework as a decision and prediction tool for linguists studying a new language. We experiment 162 grammar configurations for each language and show that using Adaptor Grammars for word segmentation enables us to test hypotheses about a language. Specializing a generic grammar with language specific knowledge leads to great improvements for the word discovery task, ultimately achieving a leap of about 30% token F-score from the results of a strong baseline.
Fichier principal
Vignette du fichier
W18-5804.pdf (637.89 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01910757 , version 1 (01-11-2018)

Identifiers

Cite

Pierre Godard, Laurent Besacier, François Yvon, Martine Adda-Decker, Gilles Adda, et al.. Adaptor Grammars for the Linguist: Word Segmentation Experiments for Very Low-Resource Languages. Workshop on Computational Research in Phonetics, Phonology, and Morphology, Oct 2018, Bruxelles, Belgium. pp.32 - 42, ⟨10.18653/v1/P17⟩. ⟨hal-01910757⟩
170 View
201 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More