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Publication . Article . 2021

Is Hanja represented in the Korean mental lexicon?: Encoding cross-script semantic cohorts in the representation of Sino-Korean

Yoolim Kim; Sandra Kotzor; Aditi Lahiri;
Open Access
Published: 01 Dec 2021 Journal: Lingua, volume 264, page 103,128 (issn: 0024-3841, Copyright policy )
Publisher: Elsevier BV
Abstract

Korean can be transcribed in two different scripts, one alphabetic (Hangul) and one logographic (Hanja). How does the mental lexicon represent the contributions of multiple scripts? Hangul’s highly transparent one-to-one relationship between spellings and sounds creates homophones in spoken Korean that are also homographs in Hangul, which can only be disambiguated through Hanja. We thus tested whether native speakers encoded the semantic contributions of the different Hanja characters sharing the same homographic form in Hangul in their mental representation of Sino-Korean. Is processing modulated by the number of available meanings, that is, the size of the semantic cohort? In two cross-modal lexical decision tasks with semantic priming,participants were presented with auditory primes that were either syllables (Experiment 1) or full Sino-Korean words (Experiment 2), followed by visual Sino-Korean full word targets. In Experiment 1, reaction times were not significantly modulated by the size of the semantic cohort. However, in Experiment 2, we observed significantly faster reaction times for targets preceded by primes with larger semantic cohorts. We discuss these findings in relation to the structure of the mental lexicon for bi-scriptal languages and the representation of semantic cohorts across different scripts. 1. Introduction 2. Hanja and Hangul during processing 3. Experiment 1: Cross-modal fragment priming 3.1. Method 3.1.1. Participants 3.1.2. Materials and design 3.1.3. Procedure 3.2. Results 3.3. Discussion 4. Experiment 2: Cross-modal full word priming 4.1. Method 4.1.1. Participants 4.1.2. Materials and design 4.1.3. Procedure 4.2. Results 4.3. Discussion 5. General discussion 6. Conclusions

Subjects by Vocabulary

Microsoft Academic Graph classification: Homophone Scripting language computer.software_genre computer Lexical decision task Hangul Representation (arts) Natural language processing Mental representation Mental lexicon Encoding (semiotics) Artificial intelligence business.industry business Psychology

Subjects

Linguistics and Language, Language and Linguistics

Funded by
EC| MOR-PHON
Project
MOR-PHON
Resolving Morpho-Phonological Alternation: Historical, Neurolinguistic, and Computational Approaches
  • Funder: European Commission (EC)
  • Project Code: 695481
  • Funding stream: H2020 | ERC | ERC-ADG
Related to Research communities
Digital Humanities and Cultural Heritage
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