On the Impact of Non-speech Sounds on Speaker Recognition

被引:0
|
作者
Janicki, Artur [1 ]
机构
[1] Warsaw Univ Technol, Inst Telecommun, PL-00665 Warsaw, Poland
来源
关键词
speaker recognition; GMM-UBM; non-speech sounds; TIMIT;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper investigates the impact of non-speech sounds on the performance of speaker recognition. Various experiments were conducted to check what the accuracy of speaker classification would be if non-speech sounds, such as breaths, were removed from the training and/or testing speech. Experiments were run using the GMM-UBM algorithm and speech taken from the TIMIT speech corpus, either original or transcoded using the G.711 or GSM 06.10 codecs. The results show a remarkable contribution of non-speech sounds to the overall speaker recognition performance.
引用
收藏
页码:566 / 572
页数:7
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