Kurtosis-based blind beamforming: an adaptive, subband implementation with a convergence improvement
Klingler, Daniel
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https://hdl.handle.net/2142/46649
Description
Title
Kurtosis-based blind beamforming: an adaptive, subband implementation with a convergence improvement
Author(s)
Klingler, Daniel
Issue Date
2014-01-16T17:57:30Z
Director of Research (if dissertation) or Advisor (if thesis)
Jones, Douglas L.
Department of Study
Electrical and Computer Engineering
Discipline
Electrical and Computer Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Speech Enhancement
Maximum Kurtosis
Subband Implementation
Convergence Improvement
Beamforming
Noise Reduction
Abstract
In many speech applications, a single talker is captured in the presence of background noise using a multi-microphone array. Without knowledge of the array geometry, talker location, or the room response, many traditional beamforming techniques cannot be used effectively. An adaptive, maximum-kurtosis objective is used in the frequency domain to blindly enhance the speech signal. The algorithm provides SNR gains of 3.5 - 7.5 dB with just two microphones in low-SNR, real-world scenarios. An improvement is presented that allows for faster and more stable convergence of the algorithm in real-time implementations. Finally, an alternative formulation to the problem is given, framing it in a way that might inspire new discussion or alternative solutions.
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