Operation LiLi: Using Crowd-Sourced Data and Automatic Alignment to Investigate the Phonetics and Phonology of Less-Resourced Languages - Archive ouverte HAL
Article Dans Une Revue Languages Année : 2022

Operation LiLi: Using Crowd-Sourced Data and Automatic Alignment to Investigate the Phonetics and Phonology of Less-Resourced Languages

Résumé

Less-resourced languages are usually left out of phonetic studies based on large corpora. We contribute to the recent efforts to fill this gap by assessing how to use open-access, crowd-sourced audio data from Lingua Libre for phonetic research. Lingua Libre is a participative linguistic library developed by Wikimedia France in 2015. It contains more than 670k recordings in approximately 150 languages across nearly 740 speakers. As a proof of concept, we consider the Inventory Size Hypothesis, which predicts that, in a given system, variation in the realization of each vowel will be inversely related to the number of vowel categories. We investigate data from 10 languages with various numbers of vowel categories, i.e., German, Afrikaans, French, Catalan, Italian, Romanian, Polish, Russian, Spanish, and Basque. Audio files are extracted from Lingua Libre to be aligned and segmented using the Munich Automatic Segmentation System. Information on the formants of the vowel segments is then extracted to measure how vowels expand in the acoustic space and whether this is correlated with the number of vowel categories in the language. The results provide valuable insight into the question of vowel dispersion and demonstrate the wealth of information that crowd-sourced data has to offer.

Domaines

Linguistique
Fichier principal
Vignette du fichier
languages-07-00234.pdf (3.29 Mo) Télécharger le fichier
Origine Publication financée par une institution

Dates et versions

hal-03778651 , version 1 (08-12-2022)

Identifiants

Citer

Mathilde Hutin, Marc Allassonnière-Tang. Operation LiLi: Using Crowd-Sourced Data and Automatic Alignment to Investigate the Phonetics and Phonology of Less-Resourced Languages. Languages, 2022, 7 (3), pp.234. ⟨10.3390/languages7030234⟩. ⟨hal-03778651⟩
197 Consultations
37 Téléchargements

Altmetric

Partager

More