Discrete-time signal processing (2nd ed.)
Discrete-time signal processing (2nd ed.)
Acoustic MIMO Signal Processing (Signals and Communication Technology)
Acoustic MIMO Signal Processing (Signals and Communication Technology)
An integrated real-time beamforming and postfiltering system for nonstationary noise environments
EURASIP Journal on Applied Signal Processing
GSVD-based optimal filtering for single and multimicrophone speech enhancement
IEEE Transactions on Signal Processing
Signal enhancement using beamforming and nonstationarity withapplications to speech
IEEE Transactions on Signal Processing
A Minimum Distortion Noise Reduction Algorithm With Multiple Microphones
IEEE Transactions on Audio, Speech, and Language Processing
New insights into the noise reduction Wiener filter
IEEE Transactions on Audio, Speech, and Language Processing
On Microphone-Array Beamforming From a MIMO Acoustic Signal Processing Perspective
IEEE Transactions on Audio, Speech, and Language Processing
Analysis and Comparison of Multichannel Noise Reduction Methods in a Common Framework
IEEE Transactions on Audio, Speech, and Language Processing
Dereverberation and Denoising Using Multichannel Linear Prediction
IEEE Transactions on Audio, Speech, and Language Processing
Direction of Arrival Estimation Using the Parameterized Spatial Correlation Matrix
IEEE Transactions on Audio, Speech, and Language Processing
Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition
IEEE Transactions on Audio, Speech, and Language Processing
Evaluation of Objective Quality Measures for Speech Enhancement
IEEE Transactions on Audio, Speech, and Language Processing
Dual-Source Transfer-Function Generalized Sidelobe Canceller
IEEE Transactions on Audio, Speech, and Language Processing
On the Importance of the Pearson Correlation Coefficient in Noise Reduction
IEEE Transactions on Audio, Speech, and Language Processing
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Several contributions have been made so far to develop optimal multichannel linear filtering approaches and show their ability to reduce the acoustic noise. However, there has not been a clear unifying theoretical analysis of their performance in terms of both noise reduction and speech distortion. To fill this gap, we analyze the frequency-domain (non-causal) multichannel linear filtering for noise reduction in this paper. For completeness, we consider the noise reduction constrained optimization problem that leads to the parameterized multichannel non-causal Wiener filter (PMWF). Our contribution is fivefold. First, we formally show that the minimum variance distortionless response (MVDR) filter is a particular case of the PMWF by properly formulating the constrained optimization problem of noise reduction. Second, we propose new simplified expressions for the PMWF, the MVDR, and the generalized sidelobe canceller (GSC) that depend on the signals' statistics only. In contrast to earlier works, these expressions are explicitly independent of the channel transfer function ratios. Third, we quantify the theoretical gains and losses in terms of speech distortion and noise reduction when using the PWMF by establishing new simplified closed-form expressions for three performance measures, namely, the signal distortion index, the noise reduction factor (originally proposed in the paper titled "New insights into the noise reduction Wiener filter," by J. Chen et al. (IEEE Transactions on Audio, Speech, and Language Processing, Vol. 15, no. 4, pp. 1218-1234, Jul. 2006) to analyze the single channel time-domain Wiener filter), and the output signal-to-noise ratio (SNR). Fourth, we analyze the effects of coherent and incoherent noise in addition to the benefits of utilizing multiple microphones. Fifth, we propose a new proof for the a posteriori SNR improvement achieved by the PMWF. Finally, we provide some simulations results to corroborate the findings of this work.