Investigating Critical Period Effects in Language Acquisition through Neural Language Models
Humans appear to have a critical period (CP) for language acquisition: Second language (L2) acquisition becomes harder after early childhood, and ceasing exposure to a first language (L1) after this period (but not before) typically does not lead to substantial loss of L1 proficiency. It is unknown whether these CP effects result from innately determined brain maturation or as a stabilization of neural connections naturally induced by experience. In this study, we use language models (LMs) to test the extent to which these phenomena are peculiar to humans, or shared by a broader class of language learners. We vary the age of exposure by training LMs on language pairs in various experimental conditions, and find that LMs, which lack any direct analog to innate maturational stages, do not show CP effects when the age of exposure of L2 is delayed. Our results contradict the claim that CP effects are an inevitable result of statistical learning, and they are consistent with an innate mechanism for CP effects. We show that we can reverse-engineer the CP by introducing a regularizer partway through training to simulate a maturational decrease in plasticity. All in all, our results suggest that L1 learning on its own may not be enough to induce a CP, and additional engineering is necessary to make language models more cognitively plausible.
Code (1)
Tasks
Language AcquisitionSimilar Papers 제목 키워드 기반
Do Self-Supervised Speech Models Exhibit the Critical Period Effects in Language Acquisition?
This paper investigates whether the Critical Period (CP) effects in human language acquisition are observed in self-supervised speech models (S3Ms). CP effects refer to greater difficulty in acquiring a second language (…
Language AcquisitionLost but not erased: Finding traces of a forgotten language in neural speech models
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 …
Language AcquisitionSpeech RecognitionDevelopmentally-plausible Working Memory Shapes a Critical Period for Language Acquisition
Large language models exhibit general linguistic abilities but significantly differ from humans in their efficiency of language acquisition. This study proposes a method for integrating the developmental characteristics …
Language AcquisitionThe Life Cycle of Knowledge in Big Language Models: A Survey
Knowledge plays a critical role in artificial intelligence. Recently, the extensive success of pre-trained language models (PLMs) has raised significant attention about how knowledge can be acquired, maintained, updated …
Developmental Predictive Coding Model for Early Infancy Mono and Bilingual Vocal Continual Learning
Understanding how infants perceive speech sounds and language structures is still an open problem. Previous research in artificial neural networks has mainly focused on large dataset-dependent generative models, aiming t…
Continual LearningLanguage Acquisition