開發高解析度多媒體系統的目的之一在於為身處不同地點的人們提供有如在另一場景般的逼真感受，而其重點在必須將人們所能看得到、聽得到、甚至觸摸得到的訊息利用資訊技術準確地擷取與再生。隨著音樂自動分析、組織與合成的需求增加，樂音分離與重建在近年來日受矚目。傳統求得空間等化器的方式為利用單一麥克風在一定點上量測由揚聲器所發出來的脈衝響應，接著求取其反函式用以修正空間頻率響應。使用這種方式的缺點為其只適用於單一聆聽點，在多數的情況下也不適合應用於多聆聽點的量測上。再者，此法對於聆聽者即便微小的移動便有失準的疑慮。有鑑於此，在本研究中我們使用度量多維標定法來等化與視覺化空間響應。此映射提供了群聚化空間響應的另一觀點，並呈現了多聆聽點等化後的一致性。更明確地說，在多維空間中訊號間的距離於降至二維平面後使得表達空間響應的群聚性變得可能。各個群組間的相似性乃基於頻譜振幅響應強度大小，而這些多樣的原型響應稍後將被用來產生單一且具概括性的點響應。此等化與分群的技術將可被用於如家庭劇院與車內空間等需多點音源控制的場合。除此之外，由於豐富的環場感來自於多方向的聲音重建，透過訊號處理、麥克風陣列與揚聲器陣列等，將使得小空間得以模擬大空間的音場。

One goal of the hi-definition multimedia systems is to create the illusion of proximity for people physically located in different areas. To achieve this, it is essen-tial to pick-up and regenerate all the crucially visual, aural, and tactile cues that are perceptible by human senses. As the demand for automatically analyzing, organizing, and synthesizing a vast amount of musical information, musical sound separation and reconstruction are getting more and more attention recently. Conventional approaches to the room equalization have used a single microphone at the listening position to measure impulse responses in sequence from a loudspeaker, and then use an inverse filter to correct the frequency response. The problem of utilizing this approach is that it only works well for the one-point scenario and in most cases is not practical enough for measuring multiple spots. Moreover, it does not function at all for other listeners in the room even though the listener changes positions slightly. In this study, we use the metric multidimensional scaling for visualizing and equalizing room responses. This mapping provides an alternative perspective on the formation of clusters of room responses and displays the uniformity of the equalized responses at multiple positions. More specifically, distances of signals in multidimensional spaces are mapped onto distances in two dimensions after dimension reduction, and therefore displaying the clustering behavior based on the room responses is possible. In addition, we use the clustering technique for finding similarities among room responses based on the strengths of magnitude responses. These prototypical responses can then be combined to create a general point response. The equalization and clustering algorithms proposed in this work find applications in the requirement of multi-point sound control such as home theater and in-vehicle environment. Since rich surrounding experience results from the reconstruction of multi-directional sounds, with the advance in microphone array, loudspeaker array and digital signal processing technologies, it is desirable and possible to simulate the sound field of a concert hall in a small space.

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