Xianyun Wang

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In this paper, we propose a frequency-domain speech enhancement algorithm with phase estimation, in which the speech model is modeled by a Gaussian mixture model (GMM) in the log-spectral domain and two closed-form log-spectral amplitude estimators for speech and noise are derived directly by using a Mixture-Maximum (MIXMAX) model. Because the accurate(More)
Large air cooling fan system is made up of many fans. The dynamic response of the fan bridge truss is very complicated when the fans are running simultaneously. Four fans and their supporting structures are selected from the fan system as analysis object. By finite element method, vibration response produced by 15 kinds of the combinations of running of(More)
Changes in the density and species composition of planktonic rotifers as well as their relationship to several environmental variables were studied at Dadian Lake, a shallow subtropical lake, which was completely dredged and reconstructed. Samples were taken monthly (2006-2009) at five stations. The total rotifer abundance exponentially declined and reached(More)
The estimation of Laplacian factor is a crucial part of speech enhancement algorithms using Laplacian model priori. Classical methods for the estimation of this parameter suffer from the residual noise or time delay bias. In this paper, a novel algorithm called two-step technique for the estimation of Laplacian factor is proposed in discrete cosine(More)
This paper provides an improved codebook-based speech enhancement method using multi-band excitation (MBE) model. It aims to remove the noise between the harmonics, which may exist in codebook-based enhanced speech. In general, the proposed system is based on analysis-withsynthesis (AwS) framework. During the analysis stage, acoustic features are extracted(More)
In most approaches based on computational auditory scene analysis (CASA), the ideal binary mask (IBM) is often used for noise reduction. However, it is almost impossible to obtain the IBM result. The error in IBM estimation may greatly violate smooth evolution nature of speech because of the energy absence in many speech-dominated time-frequency (TF) units.(More)
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