Making sense of spoken plurals
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Abstract (arXiv)
Distributional semantics offers new ways to study the semantics of morphology. This study focuses on the semantics of noun singulars and their plural inflectional variants in English. Our goal is to compare two models for the conceptualization of plurality. One model (FRACSS) proposes that all singular-plural pairs should be taken into account when predicting plural semantics from singular semantics. The other model (CCA) argues that conceptualization for plurality depends primarily on the semantic class of the base word. We compare the two models on the basis of how well the speech signal of plural tokens in a large corpus of spoken American English aligns with the semantic vectors predicted by the two models. Two measures are employed: the performance of a form-to-meaning mapping and the correlations between form distances and meaning distances. Results converge on a superior alignment for CCA. Our results suggest that usage-based approaches to pluralization in which a given word's own semantic neighborhood is given priority outperform theories according to which pluralization is conceptualized as a process building on high-level abstraction. We see that what has often been conceived of as a highly abstract concept, [+plural], is better captured via a family of mid-level partial generalizations.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 5 of its 63 references that are in the map. First posted on arXiv 5 Jul 2022.
Builds on
5 of 63 references.
References · 5
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
- 2019Distributional Semantics and Linguistic Theorycited by 53
- 2019Evaluating Word Embedding Models: Methods and Experimental Resultscited by 37
- 2021Learning Zero-Shot Multifaceted Visually Grounded Word Embeddings via Multi-Task Trainingcited by 8
- 2022Semantic properties of English nominal pluralization: Insights from word embeddingscited by 2
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.