為了找出答案，我與兩位蘭卡斯特大學語言學習研究室（Language Learning Lab）的研究者合作：語言學與認知科學教授派屈克·雷布夏特（Patrick Rebuschat），以及心理系認知學教授 帕德瑞克·莫納漢(Padraic Monaghan)。他們讓我試做一項為反映真實世界語言學習情境而設計的實驗，並揭示我們的大腦如何接收、解讀新的單字與聲音。
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Another way to look at our threshold matrix is as a kind of probability matrix. Instead of offsetting the input pixel by the value given in the threshold matrix, we can instead use the value to sample from the cumulative probability of possible candidate colours, where each colour is assigned a probability or weight . Each colour’s weight represents it’s proportional contribution to the input colour. Colours with greater weight are then more likely to be picked for a given pixel and vice-versa, such that the local average for a given region should converge to that of the original input value. We can call this the N-candidate approach to palette dithering.
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