Learning Additional Languages as Hierarchical Probabilistic Inference: Insights From First Language Processing

Bozena Pajak, Alex B. Fine, Dave F. Kleinschmidt, T. Florian Jaeger

Research output: Contribution to journalReview articlepeer-review

31 Scopus citations

Abstract

We present a framework of second and additional language (L2/Ln) acquisition motivated by recent work on socio-indexical knowledge in first language (L1) processing. The distribution of linguistic categories covaries with socio-indexical variables (e.g., talker identity, gender, dialects). We summarize evidence that implicit probabilistic knowledge of this covariance is critical to L1 processing, and propose that L2/Ln learning uses the same type of socio-indexical information to probabilistically infer latent hierarchical structure over previously learned and new languages. This structure guides the acquisition of new languages based on their inferred place within that hierarchy and is itself continuously revised based on new input from any language. This proposal unifies L1 processing and L2/Ln acquisition as probabilistic inference under uncertainty over socio-indexical structure. It also offers a new perspective on crosslinguistic influences during L2/Ln learning, accommodating gradient and continued transfer (both negative and positive) from previously learned to novel languages, and vice versa.

Original languageEnglish (US)
Pages (from-to)900-944
Number of pages45
JournalLanguage Learning
Volume66
Issue number4
DOIs
StatePublished - Dec 1 2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Education
  • Language and Linguistics
  • Linguistics and Language

Keywords

  • hierarchical probabilistic inference
  • second language acquisition
  • speech adaptation
  • statistical learning

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