LDL Index

LDL Implementations

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Final Implementation(s)
  1. Durational differences of word-final /s/ emerge from the lexicon: Modelling morpho-phonetic effects in pseudowords with linear discriminative learning
    This script documents the implementation of ENGS production data in a Linear Discriminative Learning (LDL) network. This is the implementation used in Schmitz et al. (2021).
Previous Implementations
  1. Durational differences of homophonous suffixes emerge from the lexicon: Three Analyses
    This script documents the analysis and modelling of ENGS production data with measures of Linear Discriminative Learning (LDL), introducing an updated pseudoword semantic matrix creation procedure.
  2. Durational differences of homophonous suffixes emerge from the lexicon: After Workshop
    This script documents the analysis and modelling of ENGS production data and MALD corpus data with measures of Linear Discriminative Learning (LDL).
  3. Durational differences of homophonous suffixes emerge from the lexicon: PCAs and GAMMs
    This script documents the analysis of ENGS production data and MALD corpus data with measures of Linear Discriminative Learning (LDL). The measures used in this script are found and explained in 4).
  4. Durational differences of homophonous suffixes emerge from the lexicon: Evidence from pseudowords’ semantic vectors
    This script documents the analysis of ENGS production data and MALD corpus data by means and measures of Linear Discriminative Learning (LDL). The results of this script are analyzed in 3).
  5. Durational differences of homophonous suffixes emerge from the lexicon
    First attempt of including pseudowords in Linear Discriminative Learning (LDL). This is an exploratory script without any clear results.

LDLConvFunctions Package

LDLConvFunctions offers functions to conveniently compute and extract several measures from WpmWithLdl objects. Please find the package on GitHub.

This vignette provides all necessary information on the LDLConvFunctions package, including installation instructions and examples for all functions.

All functions explicitly mentioned in this vignette which are not part of the LDLConvFunctions package are part of the WpmWithLdl package unless noted otherwise. Measures computed and extracted by functions of this package were originally introduced by Chuang et al. (2020).

The package and its functions were first used in Schmitz et al. (2021a). The Mean Word Support function is inspired by Stein & Plag (2021).

References

Baayen, R. H., Chuang, Y. Y., and Blevins, J. P. (2018). Inflectional morphology with linear mappings. The Mental Lexicon, 13 (2), 232-270. doi.org/10.1075/ml.18010.baa

Chuang, Y-Y., Vollmer, M-l., Shafaei-Bajestan, E., Gahl, S., Hendrix, P., & Baayen, R. H. (2020). The processing of pseudoword form and meaning in production and comprehension: A computational modeling approach using Linear Discriminative Learning. Behavior Research Methods, 1-51. doi.org/10.3758/s13428-020-01356-w

Schmitz, D., Baer-Henney, D., & Plag, I. (2021a). The duration of word-final /s/ differs across morphological categories in English: Evidence from pseudowords. Phonetica, 78(5-6), 571-616. 10.1515/phon-2021-2013

Schmitz, D., Plag, I., Baer-Henney, D., & Stein, S. D. (2021b). Durational differences of word-final /s/ emerge from the lexicon: Modelling morpho-phonetic effects in pseudowords with linear discriminative learning. Frontiers in Psychology. 10.3389/fpsyg.2021.680889

Stein, S.D., & Plag, I. (2021). Morpho-phonetic effects in speech production: Modeling the acoustic duration of English derived words with linear discriminative learning. Frontiers in Psychology. 10.3389/fpsyg.2021.678712

Tucker, B. V., Brenner, D., Danielson, D. K., Kelley, M. C., Nenadic, F., & Sims, M. (2018). The massive auditory lexical decision (MALD) database. Behavior Research Methods, 1-18. doi.org/10.3758/s13428-018-1056-1