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I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences

16 April 2019
Kong Aik Lee
Ville Hautamaki
Tomi Kinnunen
Hitoshi Yamamoto
K. Okabe
Ville Vestman
Jing-ling Huang
Guo-Hong Ding
Hanwu Sun
Anthony Larcher
Rohan Kumar Das
Haizhou Li
Mickael Rouvier
Pierre-Michel Bousquet
Wei Rao
Qing Wang
Chunlei Zhang
F. Bahmaninezhad
Héctor Delgado
Jose Patino
Qiongqiong Wang
Ling Guo
Takafumi Koshinaka
Jiacen Zhang
Koichi Shinoda
Trung Ngo Trong
Md. Sahidullah
Fan Lu
Yun Tang
Ming Tu
Kah Kuan Teh
T. H. Dat
Kuruvachan K. George
Ivan Kukanov
Florent Desnous
Jichen Yang
Emre Yilmaz
Longting Xu
J. Bonastre
Chenglin Xu
Zhi Hao Lim
Chng Eng Siong
Shivesh Ranjan
John H. L. Hansen
Massimiliano Todisco
Nicholas W. D. Evans
    BDL
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Abstract

The I4U consortium was established to facilitate a joint entry to NIST speaker recognition evaluations (SRE). The latest edition of such joint submission was in SRE 2018, in which the I4U submission was among the best-performing systems. SRE'18 also marks the 10-year anniversary of I4U consortium into NIST SRE series of evaluation. The primary objective of the current paper is to summarize the results and lessons learned based on the twelve sub-systems and their fusion submitted to SRE'18. It is also our intention to present a shared view on the advancements, progresses, and major paradigm shifts that we have witnessed as an SRE participant in the past decade from SRE'08 to SRE'18. In this regard, we have seen, among others, a paradigm shift from supervector representation to deep speaker embedding, and a switch of research challenge from channel compensation to domain adaptation.

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