@InProceedings{Birkholz2024_1212,
<br/>   author = {Peter Birkholz and Xinyu Zhang},
<br/>   booktitle = {Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2024},
<br/>   title = {An Investigation of Acoustic Features of the Lower Vocal Tract for Speaker Recognition .},
<br/>   year = {2024},
<br/>   editor = {Timo Baumann},
<br/>   month = mar,
<br/>   pages = {108--115},
<br/>   publisher = {TUDpress, Dresden},
<br/>   abstract  = {Speaker recognition systems often use mel-scaled cepstral coefficients
(MFCCs) as main features. In contrast to MFCCs, Godoy et al. (2015) proposed
a different type of short-term spectral analysis that provides features related to the
lower vocal tract (LVT). They are calculated as the ratio of the acoustic shorttime
spectra during the closed and open phases of the glottal oscillation cycles
based on a pitch-synchronous analysis. These features were suggested to be particularly
speaker-specific and might therefore be suitable to substitute or complement
MFCCs in speaker recognition systems. The present study investigated the benefit
of these features in an i-vector-based speaker recognition system. Using the LVT
features alone, the system achieved a speaker recognition rate of 92.3% with 63
enrolled speakers. When the LVT features were fused with conventional MFCC
features, the recognition rate was about equal to the recognition rate using MFCC
features alone (&gt; 98%).},
<br/>   isbn = {978-3-95908-325-6},
<br/>   issn = {0940-6832},
<br/>   keywords = {Paralinguistische Analysen},
<br/>   url = {https://www.essv.de/pdf/2024_108_115.pdf},
<br/>   doi = {10.35096/othr/pub-7087},
<br/>}