کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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534955 | 870308 | 2009 | 6 صفحه PDF | دانلود رایگان |
Gaussian mixture model is the conventional approach employed in speaker recognition tasks. Although it is efficient to model specific speaking characteristics of a speaker, especially in quiet environments, its performance in noisy conditions is still far from the human cognitive process. Recently, a new method of αα-integration of stochastic models has been proposed based on psychophysical experiments that suggests αα-integration is used in a human brain. In this paper, we proposed a method to extend the conventional GMM to the αα-integrated GMM (αα-GMM) to model personal speaking traits. Model parameters were re-estimated recursively based on a given data set. The experiments showed that the new approach significantly outperforms the traditional method, especially on telephony speech.
Journal: Pattern Recognition Letters - Volume 30, Issue 6, 15 April 2009, Pages 589–594