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Human and Machine Speaker Recognition on Short Trivial Events

Citation Author(s):
Miao Zhang, Xiaofei Kang, Yanqing Wang, Lantian Li, Zhiyuan Tang, Haisheng Dai
Submitted by:
Miao Zhang
Last updated:
13 April 2018 - 6:58am
Document Type:
Presentation Slides
Document Year:
2018
Event:
Presenters:
Miao Zhang
Paper Code:
Icassp2018-4525
 

In this paper, we collect a trivial event speech database that involves 75 speakers and 6 types of events, and report preliminary speaker recognition results on this database, by both human listeners and machines. Particularly, the deep feature learning technique recently proposed by our group is utilized to analyze and recognize the trivial events, leading to acceptable equal error rates (EERs) ranging from 5% to 15% despite the extremely short durations (0.2-0.5 seconds) of these events. Comparing different types of events, ‘hmm’ seems more speaker discriminative.

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