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Related Experiment Video

Updated: Jul 9, 2025

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

Obsolescence effects in second language phonological networks.

Eva Maria Luef^1,2

¹Institute of English and American Studies, University of Hamburg, Von-Melle-Park 6, 20146, Hamburg, Germany. eluef@gl-sec.com.

Memory & Cognition

|December 4, 2023

Summary

Second language acquisition shows an obsolescence effect, where older words gain fewer new phonological neighbors over time. This impacts how learners build their English lexicon, favoring newer vocabulary.

Keywords:

English as a second language Network evolution Network obsolescence Phonological network Preferential attachment

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Last Updated: Jul 9, 2025

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Area of Science:

Linguistics
Computational Linguistics
Second Language Acquisition

Background:

Phonological networks represent word relationships in a lexicon.
Preferential attachment (rich-gets-richer) often drives network growth.
Node-constrained language lexica may limit linear growth.

Purpose of the Study:

Investigate obsolescence effects in the evolving phonological network of English as a second language.
Examine how word activity and growth change over time in learner lexicons.

Main Methods:

Analysis of an evolving phonological network of English as a second language.
Examination of growth spurts and neighborhood density.
Assessment of phonological relationship strength and phonetic distance.

Main Results:

Phonological neighborhoods grow rapidly initially, then sublinearly, with limited later growth.
Learners rarely achieve native-like neighborhood densities.
Phonetically distant neighbors are incorporated earlier in acquisition.

Conclusions:

An obsolescence effect favors younger words in second language phonological networks.
Implications for L2 lexicon development include focused learning and processing in aging networks.