Subband DCT and EMD Based Hybrid Soft Thresholding for Speech Enhancement | Zendy

Erhan Deger | Zendy; Md. Khademul Islam Molla | Zendy; Keikichi Hirose | Zendy; Nobuaki Minematsu | Zendy; Md. Kamrul Hasan | Zendy

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Subband DCT and EMD Based Hybrid Soft Thresholding for Speech Enhancement

Author(s) -

Erhan Deger,

Md. Khademul Islam Molla,

Keikichi Hirose,

Nobuaki Minematsu,

Md. Kamrul Hasan

Publication year - 2014

Publication title -

advances in acoustics and vibration

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.237

H-Index - 14

eISSN - 1687-627X

pISSN - 1687-6261

DOI - 10.1155/2014/765454

Subject(s) - thresholding , discrete cosine transform , hilbert–huang transform , speech recognition , computer science , noise (video) , pattern recognition (psychology) , artificial intelligence , speech enhancement , time domain , frequency domain , white noise , mathematics , algorithm , noise reduction , computer vision , telecommunications , image (mathematics)

This paper presents a two-stage soft thresholding algorithm based on discrete cosine transform (DCT) and empirical mode decomposition (EMD). In the first stage, noisy speech is decomposed into eight frequency bands and a specific noise variance is calculated for each one. Based on this variance, each band is denoised using soft thresholding in DCT domain. The remaining noise is eliminated in the second stage through a time domain soft thresholding strategy adapted to the intrinsic mode functions (IMFs) derived by applying EMD on the signal obtained from the first stage processing. Significantly better SNR improvement and perceptual speech quality results for different noise types prove the superiority of the proposed algorithm over recently reported techniques

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