Affix substitution in Indonesian: A computational modeling approach

Author:

Denistia Karlina1ORCID,Baayen R. Harald2ORCID

Affiliation:

1. Vocational School, Universitas Sebelas Maret , Surakarta , Central Java , Indonesia

2. Department of Quantitative Linguistics , Eberhard Karls Universität Tübingen , Tübingen , Germany

Abstract

Abstract Indonesian has two noun-forming prefixes, PE- and PEN-, that often stand in a paradigmatic relation to verbal base words with the prefixes BER- and MEN-. The central question addressed in the present study is whether the form similarities between PEN- and MEN- make PEN- easier to learn compared to PE-. To address this question, we made use of a computational model, the ‘discriminative lexicon’ (DL) model. We trained this model on 2,517 word forms that were inflected or derived variants of 99 different base words. Of these word forms, 109 were nouns with PE- and 221 words were nouns with PEN-. Both the production and the comprehension networks of the model performed with high accuracy for both prefixes. However, the model was able to provide more precise predictions for PE- as compared to PEN-, implying that PE- should have a processing advantage compared to PEN-. There are two reasons for why PE- is learned more robustly than PEN-. First, PE- words tend to be longer and hence have more discriminative triphones. Second, due to cue competition with MEN-, the prefixal triphones of PEN- are less effective cues than those of PE-. A measure of functional load is proposed that helps clarify the relative importance of the triphones in the prefixes and those straddling the boundary between prefix and stem. Our results shed further light on the productivity paradox, role of junctural phonotactics, and (dis)functionality of affix substitution.

Funder

Endowment Fund for Education

ERC advanced grant

Publisher

Walter de Gruyter GmbH

Subject

Linguistics and Language,Language and Linguistics

Reference66 articles.

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3. Arndt-Lappe, Sabine. 2011. Towards an exemplar-based model of stress in English noun-noun compounds. Journal of Linguistics 47(3). 549–585. https://doi.org/10.1017/s0022226711000028.

4. Baayen, R. Harald, Yu-Ying Chuang & James P. Blevins. 2018. Inflectional morphology with linear mappings. The Mental Lexicon 13(2). 232–270.

5. Baayen, R. Harald, Yu-Ying Chuang, Elnaz Shafaei-Bajestan & James P. Blevins. 2019. The discriminative lexicon: A unified computational model for the lexicon and lexical processing in comprehension and production grounded not in (de)composition but in linear discriminative learning. Complexity 2019. 1–39. https://doi.org/10.1155/2019/4895891.

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