Speech enhancement via adaptive beamforming

• 主要作者: Shen, Huizhi
• 其他作者: Andy Khong Wai Hoong
• 格式: Theses and Dissertations
• 語言: English
• 出版: 2016
• 主題: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
• 在線閱讀: http://hdl.handle.net/10356/66088

Beamforming is an array signal processing technique for extracting signals from one or more directions while suppressing noise from other. Applications of the technique include direction-of-arrival (DOA) estimation of signal sources and directional signal enhancement. In the past decades, several beamforming approaches have been proposed. Among them, adaptive beamformer estimates the filter coefficients by utilizing knowledge of the signal and environment resulting in its popularity for a nonstationary environment. However, its performance can be degraded significantly due to large number of interferers, room reverberation, and DOA mismatch. Research work documented in this thesis aims to achieve robust speech source extraction using single or distributed microphone arrays in a non-stationary environment with time-varying background noise and multiple speech interferers. In order to reduce the sensitivity of adaptive beamformer to model mismatch, the probability of interference and/or noise occurrence is first estimated and subsequently applied to the optimization process, where only contributions from interference and noise are utilized to ensure minimum distortion of the desired speech signal. The estimated coefficients are then adjusted to relax the restriction of DOA for a reverberant environment. For single array, this probability is obtained using properties of the Hermitian angle. For distributed arrays, the mutual information provides knowledge of the presence of the common desired signal.