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Informed Spatial Filtering Based on Constrained Independent Component Analysis

  • Hendrik Barfuss
  • Klaus Reindl
  • Walter Kellermann
Chapter
Part of the Signals and Communication Technology book series (SCT)

Abstract

In this work, we present a linearly constrained signal extraction algorithm which is based on a Minimum Mutual Information (MMI) criterion that allows to exploit the three fundamental properties of speech and audio signals: Nonstationarity, Nonwhiteness, and Nongaussianity. Hence, the proposed method is very well suited for signal processing of nonstationary nongaussian broadband signals like speech. Furthermore, from the linearly constrained MMI approach, we derive an efficient realization in a (GSC) structure. To estimate the relative transfer functions between the microphones, which are needed for the set of linear constraints, we use an informed time-domain independent component analysis algorithm, which exploits some coarse direction-of-arrival information of the target source. As a decisive advantage, this simplifies the otherwise challenging control mechanism for simultaneous adaptation of the GSC’s blocking matrix und interference and noise canceler coefficients. Finally, we establish relations between the proposed method and other well-known multichannel linear filter approaches for signal extraction based on second-order-statistics, and demonstrate the effectiveness of the proposed signal extraction method in a multispeaker scenario.

Abbreviations

ICA

Independent Component Analysis

BSS

Blind Source Separation

MWF

Multichannel Wiener Filter

LCMV

Linearly Constrained Minimum Variance

DOA

Direction of Arrival

RTF

Relative Transfer Functions

SOS

Second Order Statistics

MVDR

Minimum Variance Distortionless Response

FIR

Finite Impulse Response

AIR

Acoustic Impulse Response

GSC

Generalized Sidelobe Canceler

MMI

Minimum Mutual Information

STFT

Short-Time Fourier Transform

VAD

Voice Activity Detection

SPP

Speech Presence Probability

TRINICON

TRIple-N Independent component analysis for CONvolutive mixtures

SE

Signal Extraction

NRE

Normalized RTF Estimation Error

SIR

Signal-to-Interference Ratio

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Hendrik Barfuss
    • 1
  • Klaus Reindl
    • 1
  • Walter Kellermann
    • 1
  1. 1.Chair of Multimedia Communications and Signal ProcessingFriedrich-Alexander University Erlangen-NürnbergErlangenGermany

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