A Fast Speaker Indexing Using Vector Quantization and Second Order Statistics with Adaptive Threshold Computation

被引：0
|
作者：
Biatov, Konstantin [1 ]
机构：
[1] Biatov Lab, St Augustin, Germany
来源：
11TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2010 (INTERSPEECH 2010), VOLS 1-2 | 2010年
关键词：
speaker indexing; speaker clustering; Bayesian Information Criterion; vector quantization;
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 describes an effective unsupervised speaker indexing approach. We suggest a two stage algorithm to speed-up the state-of-the-art algorithm based on the Bayesian Information Criterion (BIC). In the first stage of the merging process a computationally cheap method based on the vector quantization (VQ) is used. Then in the second stage a more computational expensive technique based on the BIC is applied. In the speaker indexing task a turning parameter or a threshold is used. We suggest an on-line procedure to define the value of a turning parameter without using development data. The results are evaluated using ESTER corpus.
引用
收藏
页码：1453 / 1456
页数：4
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