publication . Article . 2021

Implicit learning of two artificial grammars

C. Guillemin; B. Tillmann;
Open Access English
  • Published: 22 Dec 2021
  • Publisher: HAL CCSD
  • Country: France
Abstract
This study investigated the implicit learning of two artificial systems. Two finite-state grammars were implemented with the same tone set (leading to short melodies) and played by the same timbre in exposure and test phases. The grammars were presented in separate exposure phases, and potentially acquired knowledge was tested with two experimental tasks: a grammar categorization task (Experiment 1) and a grammatical error detection task (Experiment 2). Results showed that participants were able to categorize new items as belonging to one or the other grammar (Experiment 1) and detect grammatical errors in new sequences of each grammar (Experiment 2). Our findin...
Persistent Identifiers
Subjects
free text keywords: [SCCO]Cognitive science, Experimental and Cognitive Psychology, Cognitive Neuroscience, Artificial Intelligence, General Medicine, Perception, media_common.quotation_subject, media_common, Melody, Rule-based machine translation, Categorization, Computer science, Artificial intelligence, business.industry, business, Implicit learning, Natural language processing, computer.software_genre, computer, Grammar, Implicit cognition, Timbre
Related Organizations
Funded by
ANR| CeLyA
Project
CeLyA
Lyon Acoustics Centre
  • Funder: French National Research Agency (ANR) (ANR)
  • Project Code: ANR-10-LABX-0060
Communities
Digital Humanities and Cultural Heritage

Altmann, G. T. M., Dienes, Z., & Goode, A. (1995). Modality independence of implicitly learned grammatical knowledge. Journal of Experimental Psychology: Learning, Memory, & Cognition, 21, 899-912.

Bailey, T.M., Pothos, E.M. (2008). AGL StimSelect: Software for automated selection of stimuli for artificial grammar learning. Behav Res 40, 164-176. [OpenAIRE]

Bigand, E., D'Adamo, D. & Poulin, B. (in prep). The implicit learning of 12-tone music. Manuscript under preparation.

Bigand, E., Lalitte, P. & Tillmann, B. (2008). Learning music: prospects about implicit knowledge in music, new technologies and music education. (pp. 47-81) In: Polotti, P. & Rocchesso, D. (Eds). Sound to Sense: Sense to Sound, Logos Verlag: Berlin. [OpenAIRE]

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

Conway, C. M., & Christiansen, M. H. (2006). Statistical learning within and between modalities pitting abstract against stimulus-specific representations. Psychological Science, 17(10), 905-912

Destrebecqz, A., & Cleeremans, A. (2001). Can sequence learning be implicit? New evidence with the process dissociation procedure. Psychonomic Bulletin and Review, 8(2), 343-350. [OpenAIRE]

Dienes, Z., Altmann, G. T. M., Kwan, L. & Goode, A. (1995). Unconscious knowledge of artificial grammars is applied strategically. Journal of Experimental Psychology: Learning, Memory & Cognition, 21, 1322-1338.

Dienes, Z., & Perner, J. (1999). A theory of implicit and explicit knowl- edge. Behavioral and Brain Sciences, 22, 735-808.

Any information missing or wrong?Report an Issue