The NNI query-by-example system for MediaEval 2015

Jingyong Hou, Van Tung Pham, Cheung Chi Leung, Lei Wang, Haihua Xu, Hang Lv, Lei Xie, Zhonghua Fu, Chongjia Ni, Xiong Xiao, Hongjie Chen, Shaofei Zhang, Sining Sun, Yougen Yuan, Pengcheng Li, Tin Lay Nwe, Sunil Sivadas, Bin Ma, Eng Siong Chng, Haizhou Li

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2 引用 (Scopus)

摘要

This paper describes the system developed by the NNI team for the Query-by-Example Search on Speech Task (QUESST) in the MediaEval 2015 evaluation. Our submitted system mainly used bottleneck features/stacked bottleneck features (BNF/SBNF) trained from various resources. We investigated noise robustness techniques to deal with the noisy data of this year. The submitted system obtained the actual normalized cross entropy (actCnxe) of 0.761 and the actual Term Weighted Value (actTWV) of 0.270 on all types of queries of the evaluation data.

源语言英语
期刊CEUR Workshop Proceedings
1436
出版状态已出版 - 2015
活动Multimedia Benchmark Workshop, MediaEval 2015 - Wurzen, 德国
期限: 14 9月 201515 9月 2015

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