Classification and similarity analysis of fundamental frequency patterns in infant spoken language acquisition

Hiroko Kato Solvang, Masanobu Taniguchi, Tomohiro Nakatani, Shigeaki Amano

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Fundamental frequency (F0) patterns, which indicate the vibration frequency of vocal cords, reflect the developmental changes in infant spoken language. In previous studies of developmental psychology, however, F0 patterns were manually classified into subjectively specified categories. Furthermore, since F0 has sequential missing and indicates a mean nonstationarity, classification that employs subsequent partition and conventional discriminant analysis based on stationary and local stationary processes is considered inadequate. Consequently, we propose a classification method based on discriminant analysis of time series data with mean nonstationarity and sequential missing, and a measurement technique for investigating the configuration similarities for classification. Using our proposed procedures, we analyse a longitudinal database of recorded conversations between infants and parents over a five-year period. Various F0 patterns were automatically classified into appropriate pattern groups, and the classification similarities calculated. These similarities gradually decreased with infant's monthly age until a large change occurred around 20 months. The results suggest that our proposed methods are useful for analysing large-scale data and can contribute to studies of infant spoken language acquisition.

Original languageEnglish
Pages (from-to)187-208
Number of pages22
JournalStatistical Methodology
Volume5
Issue number3
DOIs
Publication statusPublished - 2008 May 1

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Keywords

  • AIC
  • Discriminant analysis for time series
  • F0 patterns
  • Language acquisition
  • Time series regression model with missing data

ASJC Scopus subject areas

  • Statistics and Probability

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