Speaker-specificity in speech production: The contribution of source and filter. (March 2023)

• Record Type: Journal Article
• Authors: Hughes, Vincent; Cardoso, Amanda; Foulkes, Paul; French, Peter; Gully, Amelia; Harrison, Philip
• Is Part Of: Journal of phonetics. Volume 97(2023)
• Publication Date: 2023-03
• Subjects: Speaker-specificity -- Speaker recognition -- Forensic speech science -- Hesitation markers -- Source-filter theory; Phonetics -- Periodicals; Phonetics -- Periodicals; Phonétique -- Périodiques; Phonetics; Periodicals; Electronic journals; 414.05
• DOI: 10.1016/j.wocn.2023.101224
• Languages: English
• ISSNs: 0095-4470

Abstract

Highlights: Considerable independence of acoustic measures of source and filter. Both source and filter encode speaker-specific information. Degree of source-filter independence is speaker-specific. Combining source and filter can produce optimal speaker recognition performance. Abstract: This study examines the extent to which speaker-specific information is encoded in different features of vocal output and the relationships between those features. A range of acoustic features, grouped as source (laryngeal voice quality measures and fundamental frequency) and filter features (formants and Mel-frequency cepstral coefficients; MFCCs), were extracted from the vocalic portion of the hesitation marker um for 90 male speakers of Standard Southern British English. Little overall correlation between the sets of features was observed, suggesting no strong interdependence between source and filter in our data. Although filter features were consistently better at discriminating between same- and different-speaker pairs compared with source features, combining source and filter has the potential of producing the lowest error rates and the strongest speaker discrimination scores. Taken together, results show that source and filter provide complementary speaker-specific information. However, the extent of the improvements in speaker discrimination performance when combining source and filter varied across speakers. We explore potential explanations for this finding and discuss the implications for source-filter theory, and for applied fields such as speaker recognition and forensic speech science.