8th Annual Conference of the International Speech Communication Association

Antwerp, Belgium
August 27-31, 2007

Noise Reduction Based on Adaptive β-Order Generalized Spectral Subtraction for Speech Enhancement

Junfeng Li (1), Shuichi Sakamoto (1), Satoshi Hongo (2), Masato Akagi (3), Yôiti Suzuki (1)

(1) Tohoku University, Japan
(2) Miyagi National College of Technology, Japan
(3) JAIST, Japan

Though spectral subtraction has widely been used for speech enhancement, the spectral order β set in spectral subtraction is generally fixed to some constants, resulting in the performance limitation to a certain degree. In this paper, we first analyze the performance of the β-order generalized spectral subtraction in terms of the gain function to highlight its dependence on the value of spectral order β. Based on the analysis results and considering the non-uniform effect of real-world noise on speech signal, we further propose an adaptive β-order generalized spectral subtraction in which the spectral order β is adaptively updated according to the signal-to-noise ratio in each critical band frame by frame as in a sigmoid function. Experimental results in various noise conditions illustrate the superiority of the proposed method with regard to the traditional spectral subtraction methods.

Full Paper

Bibliographic reference.  Li, Junfeng / Sakamoto, Shuichi / Hongo, Satoshi / Akagi, Masato / Suzuki, Yôiti (2007): "Noise reduction based on adaptive β-order generalized spectral subtraction for speech enhancement", In INTERSPEECH-2007, 802-805.