The Massive Auditory Lexical Decision (MALD) database.


Journal

Behavior research methods
ISSN: 1554-3528
Titre abrégé: Behav Res Methods
Pays: United States
ID NLM: 101244316

Informations de publication

Date de publication:
06 2019
Historique:
pubmed: 20 6 2018
medline: 29 10 2019
entrez: 20 6 2018
Statut: ppublish

Résumé

The Massive Auditory Lexical Decision (MALD) database is an end-to-end, freely available auditory and production data set for speech and psycholinguistic research, providing time-aligned stimulus recordings for 26,793 words and 9592 pseudowords, and response data for 227,179 auditory lexical decisions from 231 unique monolingual English listeners. In addition to the experimental data, we provide many precompiled listener- and item-level descriptor variables. This data set makes it easy to explore responses, build and test theories, and compare a wide range of models. We present summary statistics and analyses.

Identifiants

pubmed: 29916041
doi: 10.3758/s13428-018-1056-1
pii: 10.3758/s13428-018-1056-1
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1187-1204

Auteurs

Benjamin V Tucker (BV)

Department of Linguistics, University of Alberta, Edmonton, AB, Canada. bvtucker@ualberta.ca.

Daniel Brenner (D)

Department of Linguistics, University of Alberta, Edmonton, AB, Canada.

D Kyle Danielson (DK)

University of Toronto, Toronto, ON, Canada.

Matthew C Kelley (MC)

Department of Linguistics, University of Alberta, Edmonton, AB, Canada.

Filip Nenadić (F)

Department of Linguistics, University of Alberta, Edmonton, AB, Canada.

Michelle Sims (M)

Department of Linguistics, University of Alberta, Edmonton, AB, Canada.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH