Robust speaker identification and verification

Jia Ching Wang, Chung Hsien Yang, Jhing Fa Wang, Hsiao Ping Lee

研究成果: 雜誌貢獻期刊論文同行評審

26 引文 斯高帕斯(Scopus)

摘要

Acoustic characteristics have played an essential role in biometrics. In this article, we introduce a robust, text-independent speaker identification/verification system. This system is mainly based on a subspace-based enhancement technique and probabilistic support vector machines (SVMs). First, a perceptual filterbank is created from a psycho-acoustic model into which the subspace-based enhancement technique is incorporated. We use the prior SNR of each subband within the perceptual filterbank to decide the estimator's gain to effectively suppress environmental background noises. Then, probabilistic SVMs identify or verify the speaker from the enhanced speech. The superiority of the proposed system has been demonstrated by twenty speaker data taken from AURORA-2 database with added background noises.

原文???core.languages.en_GB???
頁(從 - 到)52-59
頁數8
期刊IEEE Computational Intelligence Magazine
2
發行號2
DOIs
出版狀態已出版 - 5月 2007

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