本論文主要來辨識說話者和唱歌者的身份。一個人不論是說話或唱歌，能讓電腦正確地識別出身份最重要的因素就是特徵參數的擷取，也就是找出一組可代表每位語者/歌者聲音特性的特徵參數，且不易受環境干擾，具有強健性，在不同的使用者和背景上都能維持一定的辨識效能。
選取重要的特徵參數後，接著進行語者/歌者識別，我們主要使用k-最近鄰居法則（k-nearest neighbor rule）來作分類的依據，但計算時間很長，所以我們在語者模型訓練上，採用了一些縮減資料的方法。資料縮減主要分為兩部份：降低資料量和降低資料維度。在降低資料量上，我們使用了一些向量量化的方法，例如：k-means、模糊c-means和學習向量量化，而在降低資料維度上，嘗試了線性識別分析法。

本論文嘗試用MATLAB語言寫出一套語者/歌者識別系統，其中特徵參數的擷取是在MATLAB中的Simulink環境下所進行的，其輸入方式是採用圖形輸入方式，因此只要了解訊號流程圖，就可以進行分析。

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