Estimation of second subglottal resonance based on F2 measurements and its application in consonant-vowel classification in Hungarian

Absztrakt

It has been shown for several languages that subglottal resonances (SGRs) play a dividing role in the
frequency space of consonants and vowels (e.g. vowels are separated into the back-front categories by
the second subglottal resonance). Consonant-vowel transitions are characterized by a regression line
(locus equation), and can be classified into distinct categories in the locus equation space, according
to their place of articulation. Several attempts have shown that the dividing lines between these
categories may be the SGRs. In this paper, the relation between CV transitions in the locus equation
space and the separating role of the subglottal resonances are further investigated. Locus equation
space of one native speaker of Hungarian is examined. Consonant-vowel transitions are classified
based on SGRs estimated from the locus equations of a subset of CV sequences. The hit rates and
false alarm rates of the classification are comparable to a baseline experiment where the subglottal
resonances were measured from accelerometer signal.