i-Vector with sparse representation classification for speaker verification
JMK Kua, J Epps, E Ambikairajah - Speech Communication, 2013 - Elsevier
Sparse representation-based methods have very lately shown promise for speaker
recognition systems. This paper investigates and develops an i-vector based sparse …
recognition systems. This paper investigates and develops an i-vector based sparse …
[PDF][PDF] Robust language recognition based on diverse features
In real scenarios, robust language identification (LID) is usually hindered by factors such as
background noise, channel, and speech duration mismatches. To address these issues, this …
background noise, channel, and speech duration mismatches. To address these issues, this …
[PDF][PDF] Investigating State-of-the-Art Speaker Verification in the case of Unlabeled Development Data.
In this study, we describe the systems developed by the Center for Robust Speech Systems
(CRSS), Univ. of Texas-Dallas, for the NIST i-vector challenge. Given the emphasis of this …
(CRSS), Univ. of Texas-Dallas, for the NIST i-vector challenge. Given the emphasis of this …
Frequency offset correction in single sideband speech for speaker verification
H Xing, PC Loizou, JHL Hansen - 2014 IEEE International …, 2014 - ieeexplore.ieee.org
Communication system mismatch represents a major influence for loss in speaker
recognition performance. While microphone and handset differences have been considered …
recognition performance. While microphone and handset differences have been considered …