本論文前端處理是參考Griffiths-Jim beamformer(GJBF)的架構，再將轉換成單一通道的訊號作後端處理，發展一個能將語音訊號中的背景雜訊抑制的有效方法。首先在固定波束形成(Fixed-beamformer)中採用時間延遲相加波束(Delay-and-Sum beamformer)，它是利用訊號在時間軸上的互相關性來預估麥克風間的時間延遲，再進行延遲相加之波束形成，希望能夠消除均值為零的背景雜訊，獲得以聲源為主的訊號，接著將Blocking Matrix改為適應性濾波器產生參考雜訊，以降低聲源訊號殘留在參考雜訊中。因為仍無法完全避免此情形產生，所以加入遞迴平均最小值方法(MCRA)對參考雜訊做進一步的雜訊預估，是以遞迴方式來估計雜訊的頻譜，運用預估局部最小值及搭配類似訊噪比的參數與臨界值來預估各頻帶是否含有語音，根據上述判斷來預估雜訊。分別得到聲源為主和雜訊為主的兩通道，然後用最基本的頻譜刪減法做語音增強。
經過前端處理之後，得到一個單通道的語音訊號，因為它仍含有雜訊，所以再做一次單通道的語音增強，這個後端處理包含遞迴平均最小值預估法(MCRA)預估雜訊及最佳化修正對數頻譜預估法(OM-LSA)去雜訊處理，OM-LSA是以含雜訊的語音訊號(noisy)為輸入，來估計一個增益函數，將輸入訊號乘上之後，能得到乾淨的語音。
最後獲得的訊號，利用反傅立業轉換及重疊相加的方法，轉回時域重建訊號波形。

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