Multi-aspect local inference for functional data: Analysis of ultrasound tongue profiles

Alessia Pini*, Lorenzo Spreafico, Simone Vantini, Alessandro Vietti

*Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in rivistaArticolo in rivistapeer review

6 Citazioni (Scopus)


Motivated by the analysis of a data set of ultrasound tongue profiles, we present multi-aspect interval-wise testing (IWT), i.e., a local nonparametric inferential technique for functional data embedded in Sobolev spaces. Multi-aspect IWT is a nonparametric procedure that tests differences between groups of functional data, jointly taking into account the curves and their derivatives. Multi-aspect IWT provides adjusted multi-aspect -value functions that can be used to select intervals of the domain that are imputable for the rejection of a null hypothesis. As a result, it can impute the rejection of a functional null hypothesis to specific intervals of the domain and to specific orders of differentiation. We show that the multi-aspect -value functions are provided with a control of the family-wise error rate and that they are consistent. We apply multi-aspect IWT to the analysis of a data set of tongue profiles recorded for a study on Tyrolean, a German dialect spoken in South Tyrol. We test differences between five different ways of articulating the uvular /r/: vocalized /r/, approximant, fricative, tap, and trill. Multi-aspect IWT-based comparisons result in an informative and detailed representation of the regions of the tongue where a significant difference occurs.
Lingua originaleEnglish
pagine (da-a)1-28
Numero di pagine28
RivistaJournal of Multivariate Analysis
Stato di pubblicazionePubblicato - 2018


  • Articulatory phonetics
  • Derivatives
  • Functional data analysis
  • Inference
  • Interval-wise error rate


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