Lost but not erased: Finding traces of a forgotten language in neural speech models
cs.CL, cs.LG
Submitted: 2026-08-26
Updated: 2026-08-26
Code: https://github.com/pplantinga/bilingual_networks
License: http://creativecommons.org/licenses/by/4.0/
The gist: 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.
Terminology
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.
Sources
- Conformer: Convolution-augmented Transformer for Speech Recognition
- Understanding intermediate layers using linear classifier probes
- Common Voice: A Massively-Multilingual Speech Corpus
- SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing
- SpeechBrain: A General-Purpose Speech Toolkit
Related papers
- Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
- Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
- Subliminal Steering: Stronger Encoding of Hidden Signals
- MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
- The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
- Untangling the Mechanisms of Misleading Context in Medical Question Answering