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Title:Kurtosis-based blind beamforming: an adaptive, subband implementation with a convergence improvement
Author(s):Klingler, Daniel
Advisor(s):Jones, Douglas L.
Department / Program:Electrical and Computer Engineering
Discipline:Electrical and Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(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.
Issue Date:2014-01-16
URI:http://hdl.handle.net/2142/46649
Rights Information:Copyright 2013 Daniel Klingler
Date Available in IDEALS:2014-01-16
Date Deposited:2013-12


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