The I4U Mega Fusion and Collaboration for NIST Speaker Recognition Evaluation 2016

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The I4U Mega Fusion and Collaboration for NIST Speaker Recognition Evaluation 2016
Title:
The I4U Mega Fusion and Collaboration for NIST Speaker Recognition Evaluation 2016
Journal Title:
Interspeech 2017
Keywords:
Publication Date:
20 August 2017
Citation:
Abstract:
The 2016 speaker recognition evaluation (SRE’16) is the latest edition in the series of benchmarking events conducted by the National Institute of Standards and Technology (NIST). I4U is a joint entry to SRE’16 as the result from the collaboration and active exchange of information among researchers from six-teen Institutes and Universities across 4 continents. The joint submission and several of its 32 sub-systems were among top-performing systems. A lot of efforts have been devoted to two major challenges, namely, unlabeled training data and dataset shift from Switchboard–Mixer to the new Call My Net dataset. This paper summarizes the lessons learned, presents our shared view from the sixteen research groups on recent advances, major paradigm shift, and common tool chain used in speaker recognition as we have witnessed in SRE’16. More importantly, we look into the intriguing question of fusing a large ensemble of sub-systems and the potential benefit of large-scale collaboration.
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Description:
© ISCA. Personal use of this material is permitted. The definitive version of this paper was published in INTERSPEECH 2017, Annual Conference of the International Speech Communication Association, August 20-24, 2017, Stockholm, Sweden
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