TY - GEN
T1 - I2R-NUS submission to oriental language recognition AP16-OL7 challenge
AU - Sun, Hanwu
AU - Lee, Kong Aik
AU - Hieu, Nguyen Trung
AU - Ma, Bin
AU - Li, Haizhou
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - This paper presents a detailed description and analysis of a joint submission of Institute for Infocomm Research (I2R) and National University of Singapore (NUS), which is the top performing system to AP16-OL7 Challenge. The submitted system was a fusion of two sub-systems: the i-vector system and GMM-SVM system, both based on state-of-the-art bottleneck feature. Central to our work presented in this paper is a language-dependent UBM GMM-SVM system and traditional i- vector polynomials expansion with SVM classifier. The FoCal toolkit was used for sub-system fusion. Experimental results show that the proposed approach achieves significant improvement over the baseline system on the development and evaluation sets. Our final submission achieve EER 0.440%, 1.09% and identification rates 98.9%, 97.6% on the development set and evaluation set, respectively.
AB - This paper presents a detailed description and analysis of a joint submission of Institute for Infocomm Research (I2R) and National University of Singapore (NUS), which is the top performing system to AP16-OL7 Challenge. The submitted system was a fusion of two sub-systems: the i-vector system and GMM-SVM system, both based on state-of-the-art bottleneck feature. Central to our work presented in this paper is a language-dependent UBM GMM-SVM system and traditional i- vector polynomials expansion with SVM classifier. The FoCal toolkit was used for sub-system fusion. Experimental results show that the proposed approach achieves significant improvement over the baseline system on the development and evaluation sets. Our final submission achieve EER 0.440%, 1.09% and identification rates 98.9%, 97.6% on the development set and evaluation set, respectively.
UR - http://www.scopus.com/inward/record.url?scp=85050474141&partnerID=8YFLogxK
U2 - 10.1109/APSIPA.2017.8282274
DO - 10.1109/APSIPA.2017.8282274
M3 - Conference article published in proceeding or book
AN - SCOPUS:85050474141
T3 - Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
SP - 1574
EP - 1578
BT - Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Y2 - 12 December 2017 through 15 December 2017
ER -