Speaker-specificity in speech production

The contribution of source and filter

Bibliographic Data

ID4771453
AuthorsVincent Hughes (0000-0002-4411-534X, University of York, corresponding author), Amanda Cardoso (0000-0001-9040-1163, University of British Columbia), Paul Foulkes (0000-0001-9481-1004, University of York), Peter French (0000-0001-7124-8896, University of York), Amelia Gully (0000-0002-8600-121X, University of York), Philip Harrison (0000-0003-3038-858X, University of York)
Year2023
Volume97
Pages101224
Publication date2023-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Phonetics (JOURNAL)
Journal identifiersISSN: 0095-4470 • E-ISSN: 1095-8576
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.wocn.2023.101224
OpenAlexW4320175785
LanguageEN
Citations received2
References cited46

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

Cepstrum · Correlation · Filter (signal processing) · Formant · Speaker diarisation · Speaker recognition · Speech recognition · Vowel · Computer Science · Mathematics · Phonetics and Phonology Research · Speech Recognition and Synthesis · Voice and Speech Disorders

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Open DOIOpen Access