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Estimating Key Speaker in Meeting Speech Based on Multiple Features Optimization
Wei Li Yanxiong Li,Qianhua He 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.4
This paper proposes to estimate key speaker in meeting speech based on multiple features optimization. First, each feature is defined and their differences between key speaker and other speakers are analyzed. Then, a decision function of multiple feature weighting is generated for estimating key speaker in meeting speech, and the genetic algorithm is used to optimize these coefficients of feature weighting. The methods are evaluated on three different meeting speech datasets. Experimental results show that the proposed optimization method obtains average accuracy of 93.3% for estimating key speaker, and gains average accuracy improvement by 9.7% and 4.1% compared with the previous method and the feature weighting method without optimization, respectively.