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Array signal processing

Fundamentals of statistical signal processing: Estimation theory: by Steven M. KAY; Prentice Hall signal processing series; Prentice Hall; Englewood Cliffs, NJ, USA; 1993; xii + 595 pp.; $65; ISBN: 0-13-345711-7

Removing noise from audio signals requires a nondiagonal processing of time-frequency coefficients to avoid producing ldquomusical noise.rdquo State of the art algorithms perform a parameterized filtering of spectrogram coefficients with empirically fixed parameters. A block thresholding estimation procedure is introduced, which adjusts all parameters adaptively to signal property by minimizing a Stein estimation of the risk. Numerical experiments demonstrate the performance and robustness of this procedure through objective and subjective evaluations.

Audio Denoising by Time-Frequency Block Thresholding

A new approach for speech enhancement based on the adaptive thresholding of the wavelet packets

The invention features an active noise reduction device (300) including an electronic signal processing circuit. The electronic signal processing circuit includes a first input (216) for accepting a first signal (104), a second input (106) for accepting a second signal, an output (112) for providing a third signal, a feed- forward path (220) from the first input to the output, and a feed- forward controller (326) for determining the control parameter (324) by calculating a control signal using the first signal and the second signal and then using the control signal to determine the control parameter. The feed- forward path includes a fixed compensation linear filter (218) and a variable compensation filter (322) having an input for receiving a control parameter that applies a selected linear filter from a family of linear filters that vary in both gain and spectral shape and are selectable by the control parameter.

Adaptive feed-forward noise reduction

A method and system for processing subband signals using adaptive filters is provided. The system is implemented on an oversampled WOLA filterbank. Inputs signals are oversampled. The system includes an adaptive filter for each subband, and the functionality of improving the convergence properties of the adaptive filter. For example, the convergence property is improved by whitening the spectra of the oversampled subband signals and/or affine projection algorithm. The system is applicable to echo and/or noise cancellation. Adaptive step size control, adaptation process control using Double-Talk detector may be implemented. The system may further implement a non-adaptive processing for reducing uncorrelated noise and/or cross-talk resistant adaptive noise cancellation.

Method and system for processing subband signals using adaptive filters

The problem of speech enhancement using wavelet thresholding algorithm is considered Major problems in applying the basic algorithm are discussed and modifications are proposed to improve the method First, we propose the use of different thresholds for different wavelet bands Next, by employing a pause detection algorithm, noise profile is estimated and the thresholds are adapted This enables the modified enhancement system to handle colored and nonstationary noises Finally, a wavelet-based voiced/unvoiced classification is proposed and implemented that can further improve the performance of the enhancement system To evaluate the system performance, we have used real-life noise types such as multi-talker babble and low-pass noises Subjective and objective evaluations show that the proposed system improves the performance the wavelet thresholding algorithm

https://www.onsemi.cn/site/pdf/Eurospeech2001_Wavel.pdf

An improved wavelet-based speech enhancement system.

Two of the major challenges in microphone array based adaptive beamforming, speech enhancement and distant speech recognition, are robust and accurate source localization and voice activity detection. This paper introduces a spatial gradient steered response power using the phase transform (SRPPHAT) method which is capable of localization of competing speakers in overlapping conditions. We further investigate the behavior of the SRP function and characterize theoretically a fixed point in its search space for the diffuse noise field. We call this fixed point the null position in the SRP search space. Building on this evidence, we propose a technique for multichannel voice activity detection (MVAD) based on detection of a maximum power corresponding to the null position. The gradient SRP-PHAT in tandem with the MVAD form an integrated framework of multi-source localization and voice activity detection. The experiments carried out on real data recordings show that this framework is very effective in practical applications of hands-free communication.

/pdf/an-integrated-framework-for-multi-channel-multi-source-85mqf51lkw.pdf

An integrated framework for multi-channel multi-source localization and voice activity detection

Performance of adaptive noise cancellation (ANC) degrades severely when uncorrelated noise components are present at the two inputs. Thus, practical background diffuse noises pose a serious problem for ANC systems. In this letter, we propose a new hybrid system that integrates subband adaptive filters (SAFs) and a Wiener filter. The hybrid system is implemented on an oversampled DFT filterbank that efficiently integrates the SAF and the Wiener filter components in the frequency-domain. Performance evaluation of the hybrid system in presence of diffuse noise interference shows that the proposed system is superior to both the Wiener filter and the SAF subsystems.

/pdf/a-hybrid-subband-adaptive-system-for-speech-enhancement-in-4urwfdllg8.pdf

A hybrid subband adaptive system for speech enhancement in diffuse noise fields

The ETSI AMR-2 VAD is rigorously evaluated in clean and noisy conditions. The VAD is then simplified and optimized for porting to an ultra low-resource DSP system using a fast oversampled DFT filterbank. The parameters of the low-resource VAD are optimized using two speakers and 6 types of noise at SNRs from -10 to 20 dB. The VAD is then tested by employing sentences from two other speakers and 12 different types of noise. Results show that the low-resource VAD offers a performance comparable to that of the ETSI VAD in both clean and noisy conditions. When deployed on a custom DSP running at a clock speed of 1.28 MHz and consuming less than 1 milliWatt of power, the low-resource VAD uses less than 30% of the available system resources.

https://www.onsemi.com/site/pdf/ICASSP2003_VAD.pdf

Hamid Reza Abutalebi

Papers

Method and system for processing subband signals using adaptive filters

An improved wavelet-based speech enhancement system.

An integrated framework for multi-channel multi-source localization and voice activity detection

A hybrid subband adaptive system for speech enhancement in diffuse noise fields

ETSI AMR-2 VAD: evaluation and ultra low-resource implementation