title: Gender identification from high-pass filtered vowel segments: the use of high-frequency energy.
abstract: The purpose of this study was to examine the use of high-frequency information for making gender identity judgments from high-pass filtered vowel segments produced by adult speakers. Specifically, the effect of removing lower-frequency spectral detail (i.e., F3 and below) from vowel segments via high-pass filtering was evaluated. Thirty listeners (ages 18-35) with normal hearing participated in the experiment. A within-subjects design was used to measure gender identification for six 250-ms vowel segments (/æ/, /ɪ /, /ɝ/, /ʌ/, /ɔ/, and /u/), produced by ten male and ten female speakers. The results of this experiment demonstrated that despite the removal of low-frequency spectral detail, the listeners were accurate in identifying speaker gender from the vowel segments, and did so with performance significantly above chance. The removal of low-frequency spectral detail reduced gender identification by approximately 16 % relative to unfiltered vowel segments. Classification results using linear discriminant function analyses followed the perceptual data, using spectral and temporal representations derived from the high-pass filtered segments. Cumulatively, these findings indicate that normal-hearing listeners are able to make accurate perceptual judgments regarding speaker gender from vowel segments with low-frequency spectral detail removed via high-pass filtering. Therefore, it is reasonable to suggest the presence of perceptual cues related to gender identity in the high-frequency region of naturally produced vowel signals. Implications of these findings and possible mechanisms for performing the gender identification task from high-pass filtered stimuli are discussed.
authors.affiliation: Department of Communication Sciences and Disorders, West Virginia University, P.O. Box 6122, Morgantown, WV, 26506, USA. jeremy.donai@mail.wvu.edu.
authors.forename: Jeremy J
authors.initials: JJ
authors.lastname: Donai
authors.affiliation: Department of Communication Sciences and Disorders, West Virginia University, P.O. Box 6122, Morgantown, WV, 26506, USA.
authors.forename: Norman J
authors.initials: NJ
authors.lastname: Lass
mesh_terms: D000161:Acoustic Stimulation / Q000379:methods*; D000328:Adult; D000704:Analysis of Variance; D003463:Cues; D005260:Female; D005783:Gender Identity; D006801:Humans; D008297:Male; D010470:Perceptual Masking; D013067:Speech Perception / Q000502:physiology*; D013997:Time Factors; D055815:Young Adult
keywords: Bandwidth; Gender; High-frequency energy; Identification; Vowels