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Please use this identifier to cite or link to this item: https://hdl.handle.net/10119/9984

Title: Psychoacoustically-motivated adaptive β-order generalized spectral subtraction based on data-driven optimization
Authors: Li, Junfeng
Jiang, Hui
Akagi, Masato
Keywords: Psychoacoustically-motivated adaptive β-order GSS
Data-driven optimization
Importance function
Speech intelligibility
Sigmoid function
Issue Date: 2008-09-23
Publisher: International Speech Communication Association
Magazine name: Proceedings of INTERSPEECH 2008
Start page: 171
End page: 174
Abstract: To mitigate the performance limitations caused by the constant spectral order β in the traditional spectral subtraction methods, we previously presented an adaptive β-order generalizedspectral subtraction (GSS) in which the spectral order β is updated in a heuristic way [10]. In this paper, we propose a psychoacoustically-motivated adaptive β-order GSS, by considering that different frequency bands contribute different amounts to speech intelligibility (i.e., the bandimportancefunction). Specifically, in this proposed adaptiveβ-order GSS, the tendency of spectral order β to change with the input local signal-to-noise ratio (SNR) is quantitatively approximated by a sigmoid function, which is derived through a data-driven optimization procedure by minimizing the intelligibility-weighted distance between the desired speech spectrum and its estimate. The inherent parameters of the sigmoid function are further optimized with the data-driven optimizationprocedure. Experimental results indicate that theproposed psychoacoustically-motivated adaptive β-order GSS yields great improvements over the traditional spectral subtraction methods with the intelligibility-weighted measures.
Rights: Copyright (C) 2008 International Speech Communication Association. Junfeng Li, Hui Jiang, Masato Akagi, Proceedings of INTERSPEECH 2008, pp.171-174.
URI: https://hdl.handle.net/10119/9984
Material Type: publisher
Appears in Collections:b11-1. 会議発表論文・発表資料 (Conference Papers)

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