Abstract

Normalization may be ineffective for phonetic category learning

Authors
  • Kasia Hitczenko (University of Maryland, College Park)
  • Reiko Mazuka (RIKEN Center for Brain Science)
  • Micha Elsner (The Ohio State University)
  • Naomi H. Feldman (University of Maryland, College Park)

Abstract

Sound categories often overlap in their acoustics, which can make phonetic learning difficult. Several studies argued that normalizing acoustics relative to context improves category separation (e.g. Dillon et al., 2013). However, recent work shows that normalization is ineffective for learning Japanese vowel length from spontaneous child-directed speech (Hitczenko et al., 2018). We show that this discrepancy arises from differences between spontaneous and controlled lab speech, and that normalization can increase category overlap when there are regularities in which contexts different sounds occur in - a hallmark of spontaneous speech. Therefore, normalization is unlikely to help in real, naturalistic phonetic learning situations.

Keywords: phonetic learning, normalization

How to Cite:

Hitczenko, K., Mazuka, R., Elsner, M. & Feldman, N. H., (2019) “Normalization may be ineffective for phonetic category learning”, Society for Computation in Linguistics 2(1), 369-370. doi: https://doi.org/10.7275/hb9d-vb25

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Published on
01 Jan 2019