近十年來，手機的整體性能不斷增強，不論是在通訊、攝影或是人機介面等，都有出色的表現，唯獨背景降噪功能未能有明顯的效果。時至今日，手機的通話品質不佳，且仍然沒有找到合適的解決方式。基於這個理由，本篇論文提出三種包含最佳化及強健估測的降噪概念來解決手機背景噪音干擾的問題。而本篇所使用的硬體主要為兩種不同類型的麥克風:第一種是全向型麥克風，裝置在手機背面用於收集所有背景噪音;而另一種是指向型麥克風，則置放於手機的正面下方，面對使用者。這兩組由麥克風所收到的訊號經由訊號白雜訊化的處理後，可藉由最小平方遞迴的方式鑑別出語音系統的數學差分方程模型。經由上述之安排，三種語音估測器設計:卡爾曼濾波器、 H2 估測器、 H∞ 估測器，將被開發完成並進一步地使用於實際手機系統背景環境噪音消除應用上。從研究成果明顯可知，上述三種估測器的開發完成可有效的消除手機環境背景噪音消除並提昇通話品質。

Nowadays, cellular phones which are used almost everywhere for communication around the world become more and more popularly and the whole performances of this device are highly improved no matter in communication, image capture, and human machine interface except for background noise reduction ability. Until now, in a noisy environment, the communication quality is still awful because the acoustic environments where people talk are quite complicated and there exists no suitable solution for it. Based on the above reasons, this research proposes three new noise reduction methodologies to solve the background noise corrupted problem of cellular phone based on optimal and robust estimation concepts. In the hardware configuration, two different type microphones are used: the first one is an omni-directional microphone embedded in rear of the cellular phone for all sound sources collection purpose, and the other (uni-directional microphone) is arranged in front of the cellular phone directly closely to the user’s mouth. Collecting signals of these two microphones are whiten first as a speech signal corrupted with a background noise which can be regarded as a white noise and mathematically modeled by recursive least square (RLS) system identification then. Based on these prior arrangements, three estimators: Kalman filter, H2 estimator and H∞ estimator, are further developed to eliminate the unwanted environment background noises. From the performance tests, obvious background noise reduction capabilities for the speech enhancement of communication quality of cellular phones are delivered in this investigation.

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