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Semantic satiation is a psychological phenomenon in which repetition causes a word or phrase to temporarily lose meaning for the listener,[1] who then perceives the speech as repeated meaningless sounds. Extended inspection or analysis (staring at the word or phrase for a long time) in place of repetition also produces the same effect.
Leon Jakobovits James coined the phrase "semantic satiation" in his 1962 doctoral dissertation at McGill University.[2] It was demonstrated as a stable phenomenon that is possibly similar to a cognitive form of reactive inhibition.[1] Before that, the expression "verbal satiation" had been used along with terms that express the idea of mental fatigue. The dissertation listed many of the names others had used for the phenomenon:
James presented several experiments that demonstrated the operation of the semantic satiation effect in various cognitive tasks such as rating words and figures that are presented repeatedly in a short time, verbally repeating words then grouping them into concepts, adding numbers after repeating them out loud, and bilingual translations of words repeated in one of the two languages. In each case, the subjects would repeat a word or number for several seconds, then perform the cognitive task using that word. It was demonstrated that repeating a word prior to its use in a task made the task somewhat more difficult.
An explanation for the phenomenon is that rapid repetition makes both the peripheral sensorimotor activity and central neural activation fire repeatedly.[citation needed] This is known to cause reactive inhibition, hence a reduction in the intensity of the activity with each repetition. Jakobovits James (1962) calls this conclusion the beginning of "experimental neurosemantics" [citation needed].
Studies that further explored semantic satiation include the work of Pilotti, Antrobus, and Duff (1997), which claimed that it is possible that the true locus of this phenomenon is presemantic instead of semantic adaptation.[3] There is also the experiment conducted by Kouinos et al. (2000), which revealed that semantic satiation is not necessarily a byproduct of "impoverishment of perceptual inputs."[4]
Jakobovits cited several possible semantic satiation applications and these include its integration in the treatment of phobias through systematic desensitization. He argued that "in principle, semantic satiation as an applied tool ought to work wherever some specifiable cognitive activity mediates some behavior that one wishes to alter."[5] An application has also been developed to reduce speech anxiety by stutterers by creating semantic satiation through repetition, thus reducing the intensity of negative emotions triggered during speech.[6]
There are studies that also linked semantic satiation in education. For instance, the work of Tian and Huber (2010) explored the impact of this phenomenon on word learning and effective reading. The authors claimed that this process can serve as a unique approach to test for discounting through loss of association since it allows the separation of the "lexical level from semantic level effects in a meaning-based task that involves repetitions of words."[7] Semantic satiation has also been used as a tool to gain more understanding on language acquisition such as those studies that investigated the nature of multilingualism.[8]
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Interlingualmachine translation is one of the classic approaches to machinetranslation.In this approach, the source language, i.e. the text to be translatedis transformed into an interlingua, i.e., an abstractlanguage-independent representation. The target language is thengenerated from the interlingua. Within the rule-based machinetranslation paradigm, the interlingual approach is an alternative tothe directapproachand the transferapproach.
Theinterlingual approach to machine translation has advantages anddisadvantages. The advantages are that it requires fewer componentsin order to relate each source language to each target language, ittakes fewer components to add a new language, it supports paraphrasesof the input in the original language, it allows both the analysersand generators to be written by monolingual system developers, and ithandles languages that are very different from each other (e.g.English and Arabic). The obvious disadvantage is that the definitionof an interlingua is difficult and maybe even impossible for a widerdomain. The ideal context for interlingual machine translation isthus multilingual machine translation in a very specific domain.
In thismethod of translation, the interlingua can be thought of as a way ofdescribing the analysis of a text written in a source language suchthat it is possible to convert its morphological, syntactic, semantic(and even pragmatic) characteristics, that is "meaning"into a target language. This interlingua is able to describe all ofthe characteristics of all of the languages which are to betranslated, instead of simply translating from one language toanother.
Sometimestwo interlinguas are used in translation. It is possible that one ofthe two covers more of the characteristics of the source language,and the other possess more of the characteristics of the targetlanguage. The translation then proceeds by converting sentences fromthe first language into sentences closer to the target languagethrough two stages. The above-mentioned system is based on the ideaof using linguistic proximity to improve the translation quality froma text in one original language to many other structurally similarlanguages from only one original analysis. This principle is alsoused in pivotmachine translation,where a naturallanguageis used as a "bridge" between two more distant languages.For example in the case of translating to Englishfrom Ukrainianusing Russianas an intermediate language
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