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Journal ArticleDOI

Convolutive Transfer Function Generalized Sidelobe Canceler

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TLDR
Experimental results demonstrate that the proposed beamformer outperforms the transfer function GSC (TF-GSC) in reverberant environments and achieves both improved noise reduction and reduced speech distortion.
Abstract
In this paper, we propose a convolutive transfer function generalized sidelobe canceler (CTF-GSC), which is an adaptive beamformer designed for multichannel speech enhancement in reverberant environments. Using a complete system representation in the short-time Fourier transform (STFT) domain, we formulate a constrained minimization problem of total output noise power subject to the constraint that the signal component of the output is the desired signal, up to some prespecified filter. Then, we employ the general sidelobe canceler (GSC) structure to transform the problem into an equivalent unconstrained form by decoupling the constraint and the minimization. The CTF-GSC is obtained by applying a convolutive transfer function (CTF) approximation on the GSC scheme, which is a more accurate and a less restrictive than a multiplicative transfer function (MTF) approximation. Experimental results demonstrate that the proposed beamformer outperforms the transfer function GSC (TF-GSC) in reverberant environments and achieves both improved noise reduction and reduced speech distortion.

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Citations
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Journal ArticleDOI

A Consolidated Perspective on Multimicrophone Speech Enhancement and Source Separation

TL;DR: This paper proposes to analyze a large number of established and recent techniques according to four transverse axes: 1) the acoustic impulse response model, 2) the spatial filter design criterion, 3) the parameter estimation algorithm, and 4) optional postfiltering.
Journal ArticleDOI

A Multichannel MMSE-Based Framework for Speech Source Separation and Noise Reduction

TL;DR: This framework starts by formulating the minimum-mean-square error (MMSE)-based solution in the context of multiple simultaneous speakers and background noise, and outlines the importance of the estimation of the activities of the speakers.
Journal ArticleDOI

Multi-channel linear prediction-based speech dereverberation with sparse priors

TL;DR: This paper proposes to model the desired speech signal using a general sparse prior that can be represented in a convex form as a maximization over scaled complex Gaussian distributions, which can be interpreted as a generalization of the commonly used time-varying Gaussian model.
Journal ArticleDOI

Multi-microphone speech dereverberation and noise reduction using relative early transfer functions

TL;DR: A novel algorithm to simultaneously suppress early reflections, late reverberation and ambient noise is presented, and a multi-microphone minimum mean square error estimator is used to obtain a spatially filtered version of the early speech component.
Journal ArticleDOI

A Two-Stage Beamforming Approach for Noise Reduction and Dereverberation

TL;DR: A two-stage beamforming approach for dereverberation and noise reduction is presented and different signal-dependent beamformers can be used depending on the desired operating point in terms of noise reduction and speech distortion.
References
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Book

Adaptive Filter Theory

Simon Haykin
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.
Journal ArticleDOI

Beamforming: a versatile approach to spatial filtering

TL;DR: An overview of beamforming from a signal-processing perspective is provided, with an emphasis on recent research.
Journal ArticleDOI

Image method for efficiently simulating small‐room acoustics

TL;DR: The theoretical and practical use of image techniques for simulating the impulse response between two points in a small rectangular room, when convolved with any desired input signal, simulates room reverberation of the input signal.
Journal ArticleDOI

An algorithm for linearly constrained adaptive array processing

O.L. Frost
TL;DR: A constrained least mean-squares algorithm has been derived which is capable of adjusting an array of sensors in real time to respond to a signal coming from a desired direction while discriminating against noises coming from other directions.
Journal ArticleDOI

An alternative approach to linearly constrained adaptive beamforming

TL;DR: A beamforming structure is presented which can be used to implement a wide variety of linearly constrained adaptive array processors and is shown to incorporate algorithms which have been suggested previously for use in adaptive beamforming as well as to include new approaches.
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