ArticleFrontiers in psychology2021
Morpho-Phonetic Effects in Speech Production: Modeling the Acoustic Duration of English Derived Words With Linear Discriminative Learning.
Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 19 citations in OpenAlex.
- Is deeper always better? Replacing linear mappings with deep learning networks in the Discriminative Lexicon Model.Linguistics vanguard : multimodal online journal · 2026Article
- Morphology beyond the morpheme: distributed processing effects in the acoustic realization of German word-final clusters.Frontiers in human neuroscience · 2026Article
- How trial-to-trial learning shapes mappings in the mental lexicon: Modelling lexical decision with linear discriminative learning.Cognitive psychology · 2023Article
- Frequency effects in linear discriminative learning.Frontiers in human neuroscience · 2023Article
- Understanding the Phonetic Characteristics of Speech Under Uncertainty-Implications of the Representation of Linguistic Knowledge in Learning and Processing.Frontiers in psychology · 2022Article
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2 authors at 1 institution in 1 country.
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Abstract
Recent evidence for the influence of morphological structure on the phonetic output goes unexplained by established models of speech production and by theories of the morphology-phonology interaction. Linear discriminative learning (LDL) is a recent computational approach in which such effects can be expected. We predict the acoustic duration of 4,530 English derivative tokens with the morphological functions DIS, NESS, LESS, ATION, and IZE in natural speech data by using predictors derived from a linear discriminative learning network. We find that the network is accurate in learning speech production and comprehension, and that the measures derived from it are successful in predicting duration. For example, words are lengthened when the semantic support of the word's predicted articulatory path is stronger. Importantly, differences between morphological categories emerge naturally from the network, even when no morphological information is provided. The results imply that morphological effects on duration can be explained without postulating theoretical units like the morpheme, and they provide further evidence that LDL is a promising alternative for modeling speech production.
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