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KMID : 1022420120040020079
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Phonetics and Speech Sciences
2012 Volume.4 No. 2 p.79 ~ p.86
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Histogram Equalization Using Background Speakers’ Utterances for Speaker Identification
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Kim Myung-Jae
Yang Il-Ho
So Byung-Min
Kim Min-Seok
Yu Ha-Jin
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Abstract
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In this paper, we propose a novel approach to improve histogram equalization for speaker identification. Our method collects all speech features of UBM training data to make a reference distribution. The ranks of the feature vectors are calculated in the sorted list of the collection of the UBM training data and the test data. We use the ranks to perform order-based histogram equalization. The proposed method improves the accuracy of the speaker recognition system with short utterances. We use four kinds of speech databases to evaluate the proposed speaker recognition system and compare the system with cepstral mean normalization (CMN), mean and variance normalization (MVN), and histogram equalization (HEQ). Our system reduced the relative error rate by 33.3% from the baseline system.
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KEYWORD
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speaker recognition, speaker identification, histogram equalization
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