Considering Performance in the Automated and Manual Coding of Sociolinguistic Variables: Lessons From Variable (ING).

English variable (ING) automated coding classification forced alignment impressionistic coding machine learning sociolinguistic variables

Journal

Frontiers in artificial intelligence
ISSN: 2624-8212
Titre abrégé: Front Artif Intell
Pays: Switzerland
ID NLM: 101770551

Informations de publication

Date de publication:
2021
Historique:
received: 31 12 2020
accepted: 23 03 2021
entrez: 17 5 2021
pubmed: 18 5 2021
medline: 18 5 2021
Statut: epublish

Résumé

Impressionistic coding of sociolinguistic variables like English (ING), the alternation between pronunciations like

Identifiants

pubmed: 33997775
doi: 10.3389/frai.2021.648543
pmc: PMC8117961
doi:

Types de publication

Journal Article

Langues

eng

Pagination

648543

Informations de copyright

Copyright © 2021 Kendall, Vaughn, Farrington, Gunter, McLean, Tacata and Arnson.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Lang Speech. 2001 Sep;44(Pt 3):377-403
pubmed: 11814219
Biometrics. 1977 Mar;33(1):159-74
pubmed: 843571

Auteurs

Tyler Kendall (T)

Linguistics Department, University of Oregon, Eugene, OR, United States.

Charlotte Vaughn (C)

Linguistics Department, University of Oregon, Eugene, OR, United States.
Language Science Center, University of Maryland, College Park, MD, United States.

Charlie Farrington (C)

Linguistics Department, University of Oregon, Eugene, OR, United States.
English Department, North Carolina State University, Raleigh, NC, United States.

Kaylynn Gunter (K)

Linguistics Department, University of Oregon, Eugene, OR, United States.

Jaidan McLean (J)

Linguistics Department, University of Oregon, Eugene, OR, United States.

Chloe Tacata (C)

Linguistics Department, University of Oregon, Eugene, OR, United States.

Shelby Arnson (S)

Linguistics Department, University of Oregon, Eugene, OR, United States.

Classifications MeSH