Paper Info
Title
A perceptually motivated stationary wavelet packet filter-bank utilizing improved spectral over-subtraction algorithm for enhancing speech in non-stationary environments
Abstract
This paper proposes a novel speech enhancement approach for a single-microphone system to meet the demand of quality noise reduction algorithms. The proposed system incorporates a perceptually motivated stationary wavelet packet filter-bank (PM-SWPFB) and improved spectral over-subtraction (I-SOS) algorithm together to enhance the speech degraded by non-stationary or colored noise environment. The PM-SWPFB is obtained by adjusting the uniformly spaced stationary wavelet packet tree in order to most closely mimic the critical-bands of the psycho-acoustic model. The PM-SWPFB is, firstly, used to decompose the input noisy speech signal into nonuniform sub-bands. Then, I-SOS algorithm is used to estimate of speech from each sub-band. The I-SOS algorithm uses a new noise estimation approach, to estimate noise power from each sub-band without the need of explicit speech silence detection. The sub-band noise estimate is updated by adaptively smoothing the noisy signal power. The smoothing parameter is controlled by a function of the estimated signal-to-noise ratio (SNR). The performance of the proposed speech enhancement system is evaluated objectively by SNR, Itakura-Saito distortion measure and subjectively by informal listening test. The results confirm that the proposed speech enhancement system is capable of reducing noise with little speech degradation remains acceptable in real-world environments, and the overall performance is superior to several competitive methods.
Year
DOI
Venue
2012
10.1109/IHCI.2012.6481840
Intelligent Human Computer Interaction
Keywords
Field
DocType
channel bank filters,signal denoising,speech enhancement,wavelet transforms,I-SOS algorithm,Itakura-Saito distortion measure,PM-SWPFB,SNR,colored noise environment,estimated signal-to-noise ratio,explicit speech silence detection,improved spectral over-subtraction algorithm,informal listening test,input noisy speech signal decomposition,noise estimation approach,nonstationary environments,perceptually motivated stationary wavelet packet filter-bank,psychoacoustic model,quality noise reduction algorithms,single-microphone system,speech enhancement approach,subband noise estimate,uniformly spaced stationary wavelet packet tree,critical-band rate scale,noise estimation,spectral-over subtraction,speech enhancement,stationary wavelet packet transforms
Speech enhancement,Noise reduction,Noise power,Colors of noise,Noise measurement,Computer science,Algorithm,Speech recognition,Smoothing,Wavelet packet decomposition,Wavelet
Conference
ISBN
Citations 
PageRank 
978-1-4673-4367-1
0
0.34
References 
Authors
7
2
Name
Order
Citations
PageRank
Navneet Upadhyay100.34
Abhijit Karmakar201.35