Transposed letter effect are letter-position specific when detecting words, so our recognition of words is based on what letters it contains, where the letters are placed within that word and the length of the word itself. Another example is the bayesian reader model created by Norris (2006) which also assumes that the letters in a word are associated with their specific location. Many experiments (for example, Perea and Lupker, 2003) have shown if you use transposed-letter priming, (for example, priming judge with jugde) you will see a priming effect but if the prime is a word where two letters are changed to other
Representation (arts) example, in English the written letter "a" represents different phonetic sounds depending on which word it is written in. The letter "a" has a different sound in the word in each of the following words, "apple", "gate", "margarine" and "beat", therefore, how is a person unaware of the phonemic sounds, able to pronounce the word properly by simply looking at alphabetic spelling. The way the word is represented on paper is not always the way the word would be represented phonetically. This leads to common misrepresentations of the phonemic sounds of speech and suggests that the writing system does not