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：
TEXT, SPEECH AND DIALOGUE, TSD 2012 | 2012年 / 7499卷
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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