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This paper addresses the problem of adaptive filtering for acoustic echo cancellation in noisy and non-linear environments. The first contribution relates to a new analysis on the comparative impact of additive noise and non-linear echo on the performance of adaptive filtering for linear acoustic echo cancellation (AEC). A comprehensive performance assessment is reported, including echo return loss...
In this paper we present a speech enhancement method in highly non-stationary noise environments based on modified Improved Minimal Controlled Recursive Averaging (IMCRA) method and Optimal Modified Minimum Mean-Square Error Log-Spectral Amplitude (OMLSA) method. The original OMLSA method, the spectral gain function, which minimizes the mean-square error of the log-spectral amplitude, is obtained...
This paper proposes innovative multi-channel bayesian estimators in the feature-domain for robust speech recognition. Both minimum-mean-squared-error (MMSE) and maximum-a-posteriori (MAP) criteria have been explored: the related algorithms extend the multi-channel frequency-domain counterparts and generalize the single-channel feature-domain MMSE solution, recently appeared in the literature. Computer...
Most speech enhancement algorithms heavily depend on the noise power spectral density (PSD). Because this quantity is unknown in practice, estimation from the noisy data is necessary. We present a low complexity method for noise PSD estimation. The algorithm is based on a minimum mean-squared error estimator of the noise magnitude-squared DFT coefficients. Compared to minimum statistics based noise...
We present a dual-channel noise reduction method for small mobile devices. Our method incorporates phase difference between channels into the conventional MMSE spectral amplitude estimator. It is possible to suppress unwanted directional noise signals, whose incident direction is different from that of the target speech signal. Experimental results show that the proposed method outperformed conventional...
This paper addresses the problem of single speech enhancement in adverse environment. We propose a new speech enhancement system based on perceptual properties of human auditory ear using non-uniform and multi-band analysis. The noisy signal is divided into a number of sub-bands using a gammatone filter bank with non-linear Equivalent Rectangular Bandwidth (ERB) resolution, this sub-bands are individually...
This paper proposes an algorithm improved over MMSE-LSA Algorithm. It suits non-stationary noise environments better than the traditional algorithm. The main part of this method is the estimation of noise, which is updated using time-frequency smoothing factors calculated based on speech-present probability in each frequency bin of the noisy speech spectrum. It could keep up with the noise change...
We propose an efficient and effective nonlinear feature domain noise suppression algorithm, motivated by the minimum mean square error (MMSE) optimization criterion. Multi layer perceptron (MLP) neural network in the log spectral domain minimizes the difference between noisy and clean speech. By using this method as a pre-processing stage of a speech recognition system, the recognition rate in noisy...
Traditional noise reduction methods usually are based on the assumption that the short-term statistical distributions of speech and noise are different. Differently from that assumption, we have proposed a noise reduction method based on the assumption that the temporal modulations of noise and speech are different. Two steps are used in the proposed algorithm: one is the temporal modulation contrast...
This paper proposes a robust adaptive algorithm for adjusting coefficients of an adaptive filter, which is used in active noise canceller (ANC). The filtered LMS algorithm, which is widely used in digital signal processing, is deployed to reduce the effect of acoustic interference in a noisy environment. In this paper the zero noise output of the proposed one and two stages dual predictive line ANC...
Correntropy has been recently defined as a localised similarity measure between two random variables, exploiting higher order moments of the data. This paper presents the use of correntropy as a cost function for minimizing the error between the desired signal and the output of an adaptive filter, in order to train the filter weights.We have shown that this cost function has the computational simplicity...
The disturbance picked up by error microphone can significantly degrade the steady-state performance of active noise control (ANC) systems. Previously a cascading algorithm has been proposed, where a supporting adaptive filter is used for removing the uncorrelated disturbance from the error signal of filtered-x least mean square (FxLMS) algorithm. We modify this algorithm to improve the performance...
The excess mean squared errors is the major disadvantage in speech denoising algorithm based on least mean square, which increase linearly with the desired signal power. In order to improve the performance of the speech which exhibits in large power fluctuations, a new adaptive speech denoising algorithm based on adaptive least mean square is proposed, the improved speech denoising algorithm solve...
This paper presents an enhanced stochastic mapping technique in the discriminative feature (fMPE) space that exploits stereo data for noise robust LVCSR. Both MMSE and MAP estimates of the mapping are given and the performance of the two is investigated. Due to the iterative nature of the MAP estimate, we show that combining MMSE and MAP estimates is possible and yields superior performance than each...
In this paper, we reveal new findings about the generated musical noise in minimum mean-square error short-time spectral amplitude (MMSE STSA) processing. Recently we have proposed a objective metric of musical noise based on kurtosis change ratio on spectral subtraction (SS). Also we found an interesting relationship among the degree of generated musical noise, the shapes of signal-s probability...
This paper demonstrates a speech enhancement system based on an efficient auditory coding approach, coding of time-relative structure using spikes. The spike coding method can more compactly represent the non-stationary characteristics of speech signals than the Fourier transform or wavelet transform. Enhancement is accomplished through the use of MMSE thresholding on the spike code. Experimental...
Recently we have developed a non-linear feature-domain noise reduction algorithm based on the minimum mean square error (MMSE) criterion on Mel-frequency cepstra (MFCC) for environment-robust speech recognition. Our novel algorithm operates on the power spectral magnitude of the filter-bank's outputs and outperforms the log-MMSE spectral amplitude noise suppressor proposed by Ephraim and Malah in...
Speech controlled applications are now becoming more and more practical due to advances in technology. These applications vary from command and control instruments, video conferencing to robotics. However, their performance decreases when the acquired speech signal is corrupted by background noise. Numerous research has been done in the last two decades to improve their performance. The switched Griffiths-Jim...
Gain function of traditional enhancement algorithm is to estimate every signal spectral component, therefore, this introduce relatively more speech distortion. To improve the effect of speech enhancement at low signal-to-noise ratio (SNR), this paper proposed a optimal speech enhancement scheme. Based on auditory perception properties, no estimator for noise masked spectrum and classical enhancement...
This paper proposes a two stage hybrid speech enhancement system with nonuniform subbands. Frequency bins after Fourier transform are nonuniformly grouped to reduce the computations in calculating the spectral gain. First stage includes a soft decision gain modification and applied to the Ephraim-Malah gain function based on minimum mean square error estimation (MMSE) and a psychoacoustic masking...
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