Abstract
AbstractThis article deals with a new approach to the text-independent speaker verification task. It is namely proposed to combine spectral and the so-called high-level features (prosodic, articulatory, and lexical) in order increase accuracy of speaker verification. The presented experiments were performed using a Polish language corpus called PUEPS. It contains semi-spontaneous telephone conversations (acted emergency telephone notifications) recorded in laboratory conditions. As the Polish language is under resourced and the PUEPS corpus is relatively small, another approach is needed than these known from the well known NIST evaluations. The authors proposed to use the fast scoring instead of more complex classifiers and the AdaBoost algorithm for features combination. Combination of features resulted in equal error rate (EER) reduction for various SNR conditions.KeywordsSpeaker recognitionhigh-level featureskernel combinationboosting
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
