数据采集与处理2011，Vol.26Issue(5)：573-578,6.
结合模型混淆度和BIC准则的语种识别精细建模方法
Language Identification Based on Combination of Model Confusion and BIC Criteria
摘要
Abstract
In language identification, the detailed annotations can make the model parameters estimate more accurately, but these annotations are difficult to be acquired. This paper proposes a kind of model parameters estimation method based on language model confusion, combining Bayesian information criterion (BIC) for model selection, avoid acquiring large annotations. In NIST07 language recognition for 30, 10 and 3 s test tasks, we presented performance comparison in the maximum likelihood (ML) criterion and the maximum mutual information (MMI) criterion, our proposed method have significantly improvement, and reach the same level as using annotations.关键词
语种识别/贝叶斯信息准则/模型混淆度/高斯混合模型Key words
language identification/ Bayesian information criteria (BIC)/ model confusion/Gaussian mixture model分类
信息技术与安全科学引用本文复制引用
徐颖,宋彦,戴礼荣..结合模型混淆度和BIC准则的语种识别精细建模方法[J].数据采集与处理,2011,26(5):573-578,6.基金项目
安徽省自然科学基金(090412056)资助项目. （090412056）
