title: Speaker-dependent characteristics of the nasals.
abstract: Investigation on human speaker identification enables us to know the indexical cues to speakers, and it may consequently lead to the effective acoustical parameters that can be used for forensic speaker recognition. It is known that speaker individuality interacts with the phonological or linguistic information contained in speech signals. As proof, the accuracy of perceptual speaker identification (PSI) performances depends on what types of sounds are presented to the listeners. In a series of our previous experiments, we have been investigating the effective sounds for PSI, and the stimuli containing a nasal were found to be the ones. In this present study, we conducted another PSI experiment in order to examine the reproducibility of the nasal effectiveness, and to see the effects of the following vowels. Coronal nasals were shown to be effective despite the different speaker set or the following vowels, and the stimuli containing a nasal were significantly better than those without it. In the second part of this paper, we introduce the results of the acoustical analysis of the stimuli. The contours of the energy transitions showed variations in shape among speakers for all three types of the analysis targets; nasals, stops, and fricatives, although the inter-speaker difference in the energy slopes for the consonant articulation was significant especially in nasal sounds. We also examined the effects of the sampling frequencies and the speech codecs, and found that the speaker-dependent shapes of these energy contours were maintained as long as the speech materials were uncompressed. The contours of the nasals appeared to be stable within a speaker, compared to other types of sounds.
authors.affiliation: Faculty of Science and Technology, Department of Electrical and Electronics Engineering, Sophia University, Tokyo, Japan. amino-k@sophia.ac.jp
authors.forename: Kanae
authors.initials: K
authors.lastname: Amino
authors.forename: Takayuki
authors.initials: T
authors.lastname: Arai
mesh_terms: D000328:Adult; D005260:Female; D006801:Humans; D008297:Male; D010700:Phonetics; D013060:Speech; D014831:Voice