A joint speech signal enhancement based on singular value decomposition filter after spectral subtraction (SSVD) is proposed in this paper. The residual noise after spectral subtraction, which results for audible musical noise, is reduced further by SVD filter. The matrix size in spectral domain can be reduced half, and larger step-length adopted by SVD filter in spectral domain leads to lower ...

We propose a blind dereverberation method based on spectral subtraction using a multi-channel least mean squares (MCLMS) algorithm for distant-talking speech recognition. In a distant-talking environment, the channel impulse response is longer than the short-term spectral analysis window. By treating the late reverberation as additive noise, a noise reduction technique based on spectral subtrac...

this report shows the author’s work on audio restoration based on DSP tools from and outside of the course of EECS 451, such as moving average system, spectral subtraction method, and LMS adaptive filter design, in order to repair the degraded sound signals by reducing impulse interference, echo effects and background noise. These approaches are achieved on MATLAB, and have shown impressive res...

In noisy environments, speech recognition accuracy degrades significantly. Speech enhancement algorithms have been designed to overcome this, however solutions to date have not been optimal for speech recognition especially for non-stationary noise like that in a car. Recently, a likelihood-maximising (LIMA) criteria has been applied to speech enhancement techniques. This paper analyses the sui...

Spectral subtraction (SS) is derived using maximum likelihood estimation assuming both noise and speech follow Gaussian distributions and are independent from each other. Under this assumption, noisy speech, speech contaminated by noise, also follows a Gaussian distribution. However, it is well known that noisy speech observed in real situations often follows a heavytailed distribution, not a G...

This paper presents a new approach to robust speech recognition in noise based on spectral subtraction. A conventional spectral subtraction technique leads to nonlinear distortions of the normalized speech signals and resulting degradation of speech recognition accuracy. A new method is proposed to constrain spectral subtraction by imposing upper bounds on the estimates of the noise spectra. Tw...

In this paper, a generalized spectral subtraction approach for reducing additive impulsive noise, narrowband signals, white Gaussian noise and direct sequence code division multiple access (DS-CDMA) interferences in multiple input multiple output (MIMO) channel DS-CDMA wireless communication systems is investigated. The interference noise reduction or suppression is essential problem in wireles...