2009 International Conference on Information and Automation 2009
DOI: 10.1109/icinfa.2009.5205092
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Speech enhancement using transfer function ratio beamformer and matched filter array

Abstract: Human machine interface for speech processing often suffers from interferences which contain nonstationary signal, stationary signal and reverberation. In this paper, we consider two speech sources in the reverberant and noisy environment and we develop a speech enhancement approach to extract desired speech signal from the corrupt observations. The proposed method uses transfer function ratio beamformer, f H adaptive filter algorithm and matched filter array to perform speech enhancement as well as dereverber… Show more

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(1 citation statement)
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“…In other words, when a signal y[n] is composed of the sum of the noise-free audio signal x[n] and noise signal n[n], the goal is to restore y[n] to a form similar to x[n]. Methods such as the Wiener [36], matched [37], and Kalman filters [38] have been applied to achieve speech enhancement. Recently, with the advancement of deep learning technologies, various deep-learning-based speech enhancement techniques have received attention.…”
Section: B Speech Enhancementmentioning
confidence: 99%
“…In other words, when a signal y[n] is composed of the sum of the noise-free audio signal x[n] and noise signal n[n], the goal is to restore y[n] to a form similar to x[n]. Methods such as the Wiener [36], matched [37], and Kalman filters [38] have been applied to achieve speech enhancement. Recently, with the advancement of deep learning technologies, various deep-learning-based speech enhancement techniques have received attention.…”
Section: B Speech Enhancementmentioning
confidence: 99%