Unsupervised speaker change detection using probabilistic pattern matching
Unsupervised speaker change detection using probabilistic pattern matching
复制标题
使用概率模式匹配的无监督说话人变化检测
DOI：
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发表时间：
2006
影响因子：
3.9
通讯作者：
J. Fortuna
中科院分区：
文献类型：
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作者：
A. Malegaonkar;A. Ariyaeeinia;P. Sivakumaran;J. Fortuna
这封信提出了对使用概率模式匹配方法来检测音频流中的说话人变化的调查。实验使用干净的语音和广播新闻材料进行。结果表明，在提出的方法中，使用双侧评分比单侧评分有效得多。研究中考虑了适当的评分归一化方法。观察到，在所有情况下，双边评分方法都优于目前流行的贝叶斯信息准则（BIC）方法用于说话人变化检测。这封信讨论了所提出的方法的原理和详细的实验研究
This letter presents an investigation into the use of a probabilistic pattern matching approach for detecting speaker changes in audio streams. The experiments are conducted using clean speech as well as broadcast news material. It is shown that, in the proposed approach, the use of bilateral scoring is considerably more effective than unilateral scoring. Appropriate score normalization methods are considered in the study. It is observed that in all the cases, the bilateral scoring approach outperforms the currently popular method of Bayesian information criterion (BIC) for speaker change detection. This letter discusses the principles of the proposed approach and details the experimental investigations