Anaïs Chanclu, Imen Ben Amor, Cédric Gendrot, Emmanuel Ferragne,
Jean-François Bonastre
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Summary
Voice quality is known to be an important factor for the characterization of a speaker’s voice, both in terms of physiological features (mainly laryngeal and supralaryngeal) and of the speaker’s habits (sociolinguistic factors). This paper is devoted to one of the main components of voice quality: phonation type. It proposes neural representations of speech followed by a cascade of two binary neural network-based classifiers, one dedicated to the detection of nonmodal vowels and one for the classification of nonmodal vowels into creaky and breathy types. The performance obtained by the proposed classifiers pave the way for a new workflow aimed at characterizing phonation types
