Kurtosis-based blind beamforming: an adaptive, subband implementation with a convergence improvement

Speech Enhancement;Maximum Kurtosis;Subband Implementation;Convergence Improvement;Beamforming;Noise Reduction

Klingler, Daniel ; Jones ; Douglas L.

关键词: Speech Enhancement;    Maximum Kurtosis;    Subband Implementation;    Convergence Improvement;    Beamforming;    Noise Reduction;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/46649/Daniel_Klingler.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

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.