A Meditation on Noise and Signals (2023) 媒材：單頻道錄像與聲音裝置 尺寸：依場地而定 “One man’s noise is another’s information.” 「一個人的噪聲是另一個人的資訊。」 ——Terrence W. Deacon 據說，老式的類比電視機在沒有信號時所產生的雜訊雪花中，可能包含了1%來自遙遠外太空、宇宙微波背景輻射 (cosmic microwave background) 的信號。令人難以想像的是，自宇宙大爆炸所遺留下來的原始生命暗碼一直以一種全方位背景噪聲的形式遍佈於這個世上，無法被過濾亦無法被察覺，直到在二十世紀由科學家們利用微波天線探測到後方才轉變為「資訊」。 信噪比 (signal-to-noise ratio)，又稱訊噪比，是一種方便於我們用來比較所需訊號強度與背景噪聲強度的度量。然而，究竟何謂噪聲、何謂訊號，似乎並不存在一個固定標準，而全然取決於不同的應用情況與需求而定。 有趣的是，在聲學中，白噪音的頻譜當中包含了所有聲音頻率，也就是說，它實際上是一個充滿了可能性的潛在訊息場，理論上世界上的任何旋律都已經存在於白噪音當中。在最近發展出的擴散模型 (diffusion model) 圖像生成技術中，則透過在原圖上不斷添加一系列高斯噪聲 (Gaussian noise) ，使其變成一個「純噪點圖」，再逐步減小噪聲強度，恢復與逆推出原圖樣貌。從此，A.I.學會了如何在「純噪點」中辨識與提取影像資訊。 在這個資訊爆炸、「超限」的時代，如何從噪聲場中擷取出對我們真正有幫助的資訊，或是將不必要的資訊作為噪聲「去噪」，似乎成為了一門藝術。或許，當我們學會這門藝術，方才可以在海量的噪聲／訊息原始湯中找到屬於自己的一片安寧。 / 本作品分為視覺與聲音兩個部分，以極簡如謎的藝術語彙與風格呈現。在單頻道的八段式視覺影像投影當中，一系列清晰的原始圖像經由特意「噪聲化」的處理，轉化成抽象、迷離、不斷幻化而充滿不確定感的影像。與此同時平行進行的聲音軌道中，則透過「降噪」手法，將一段嘈雜的噪聲音頻轉化成富有旋律性與節奏性的「音樂」。透過這種手法上的錯置，訊息與雜訊之間的框架與界線被打破與重新詮釋，編織出一場沈浸式與冥想式的視覺聲響體驗。 It is rumored that the static noise on old analog TV screens may contain signals from the cosmic microwave background radiation emitted from the distant outer space. It is astounding to imagine that the code for the primordial origins of life and existence, dating back to the Big Bang, has been pervasive all around the universe in the form of a background noise that cannot be filtered out nor detected. It wasn’t until the 20th century that scientists using microwave antennas were able to discover this noise, which then immediately turned into valuable “information” to the human race. The signal-to-noise ratio (SNR) is a measure that compares the level of a desired signal to the level of background noise. However, what actually constitutes a signal or noise is actually entirely subjective and context-dependent, lacking a universal standard or definition. Interestingly, in acoustics, all frequencies are contained within the sound spectrum of white noise. Thus, theoretically, and with a slight stretch of the imagination, every song and melody you will ever hear already exists within white noise. In the recently developed Diffusion Model image generation technology, on the other hand, a series of Gaussian noise is added to an original image, turning it into a "pure noise map". The intensity of the noise is then gradually reduced in order for the program to restore and deduce the original image. Hence, A.I. has learned to recognize and extract image signals from a map of "pure noise". In the current age of information, how to extract desired and relevant information and to filter out unnecessary signals from a noise field seem to have become an art form of its own. Perhaps, it is only when we learn to master this art that we may find inner peace amidst the sea of noise in this world. / This work includes the visual and audio component. In the single-channel video projection, a series of clear images are intentionally "noisified" and transformed into an abstract, constantly changing and elusive landscape. In the audio track, white noise is transformed into a piece of melodic and rhythmic "music" through noise reduction techniques. Through the juxtaposition between these two methods, the boundary between noise and signals are broken is reinterpreted, weaving together an immersive and meditative audio-visual experience. Video Design: Jade Lien Sound Design: Jett Lien