Lost but not erased: Finding traces of a forgotten language in neural speech models

2026-08-26

AI Summary

研究使用自动语音识别模型模拟国际收养者经历，探讨早期语言痕迹在第二语言学习中的持久性及功能，揭示经验在语言习得关键期的作用。

Abstract

International adoptees retain phonological traces of a birth language they can no longer speak or comprehend, a persistence typically attributed to a biologically-timed critical period. We asked whether it could instead reflect the ordinary dynamics of learning, using automatic speech recognition models that simulate the international adoptee experience without maturational confounds. Models were trained on one language and then abruptly switched to a second. We found that traces of the first language persisted throughout second-language training, but mainly in the lowest, pre-phonemic layers. These traces were functional, as models with early exposure re-learned their lost first language 14% faster than naive models; this advantage held even against models adopted early from a related language and disappeared when the earliest layers were substituted from a non-adopted model. We argue that these critical-period effects reflect entrenchment of foundational representations rather than a maturational loss of plasticity, and that experience plays a central role in critical periods in language acquisition.

Problem

• phonological traces
• international adoptees
• critical period
• language acquisition

Innovation

• automatic speech recognition
• phonological traces
• critical period
• language re-learning
• neural models