1
Unconscious effect of translation on the
Tip-of-the-Tongue Experiences in Korean-English bilinguals
Ji Yoon Park
Advisor: Mr. Seiple, Ms. Soles
Directed Research Project
Bugil Academy GLP
September 2013
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Introduction
The tip-of-the-tongue experience (TOT) has intrigued psychologists and neuroscientists for nearly half
a century. Since Brown and McNeill (1966) provided the initial framework of it, TOT is commonly defined as a
state when the word is known, but the person is temporarily unable to access it. TOT states are hard to measure
under close experimental scrutiny since word retrieval is rapid and sporadic; therefore, the primary challenge for
researchers is to evoke them. This paper will assess TOT incidence in laboratory retrieval tasks and study the
percentages of total retrieval attempts. Many psychological and linguistic approaches have been used to study
the cause of the TOT phenomenon, including emotional influence, differences in age, or the dimensions of the
target word, such as its letter positions, number of syllables, syllabic stress, etc. (*reference) R. Brown and
McNeill suggest that TOTs are a nearly universal experience, frequently elicited by proper names, increase in
older age, often accompanied by words related to the target, and are sometimes resolved during the experience
(S. Brown, 1991). TOT incidence is also thought to increase in bilinguals than in monolinguals (Gollan &
Silverberg, 2001). A number of papers have studied models of bilingual language processing, which assume four
levels of representation: semantic, lexical (sometimes included in the semantic level), and phonological (if
spoken) or orthographic (if written). However, this paper will investigate the existence of TOT states in KoreanEnglish bilinguals by looking into both investigations of the linguistic and neural models of TOT that analyze
the influence of lexical representations and specific regions in the brain on the frequency of TOT states. This
paper then attempts to analyze translation as a factor that unconsciously influences word retrieval, and further
compare how information is processed on semantic, lexical and phonological levels.
Linguistic Models of TOT
There are mainly four accounts of the linguistic models of the TOT phenomenon.
The first account is the selected-lemma account. According to this view, TOTs entail intact lemma
selection but failed lexeme selection. (Acenas & Gollan, 2004). In other words, access to information about the
TOT target word arises from the partial activation of the target lexeme. Although there is much debate about
how many lexical representations are involved in speech production, most models postulate the existence of two
lexical levels. Lemma is the level in which syntactic information is accessed and lexical selection takes place,
and lexeme is the level where formal information is retrieved (Colome, 2001). This account predicts that
participants in a TOT state should be able to report the syntactic feature of the target word at greater
probabilities (Levelt, 1989). This model, however, lacks an explanation of why lexical links arise specifically at
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the lexeme level. Since noncognate translation equivalents are semantically related, it is hard to believe that
lexical links arise at the lexeme level, where word forms are represented. This paper, thus, neglects this model
as it is insufficient to explain language production in bilinguals.
The second model is the failed-single-selection account, which argues that TOTs reflect a complete
failure of lexical selection. TOTs occur when activation of the lexical node is high but not sufficient enough to
permit selection. For example,
The third model is called the transmission deficits account. This account does not identify TOT as a
failure to select some type of word representation, but argues that TOT occurs at a later locus of retrieval. This
model argues that TOT arises after lexical selection, which is also argued by the selected-lemma account, and
also assumes only one layer of lexical representation, which is similar to how the failed-single-selection account
incorporates the node structure theory, a model of language production. This model specifically explains why
older adults report more TOTs, because all connections throughout the lexical system are hypothesized to
weaken in older age. TOT arises after lexical selection, but the selection of lexical nodes is supported by
multiple connections from the semantic system, thus it is more vulnerable to older adults. This account also
validates the increased frequency of TOT state for bilinguals since bilingualism leads to decreased use of
language-specific connections relative to monolinguals and connection strength depends on the frequency of use.
Thus, bilinguals are less able to activate representations in each language.
The last model is called the cross-language interference account, which argues that bilinguals must
overcome direct competition from the non-target language. In 1998, Hermans, Bongaers, De Bot, and Schreuder
demonstrated that Dutch-English bilinguals were slower to name a picture in English (their second language)
when distracter words were phonologically related to the translation equivalent in either language. They also
suggested that translation equivalents compete for selection even when only one language is overtly being used.
This account then leads to an interesting prediction that if cross-language competition for activation does
increase TOT rates, then bilinguals should have more TOTs for words that they know in both languages.
However, findings in Catalan-Spanish bilinguals were inconsistent with the cross-language interference
hypothesis. Costa, Miozzo, and Caramazza (1999) demonstrated that translation equivalents facilitated retrieval
during the picture-word interference task. They suggested that although nontarget language translation
equivalents are active during production, translation equivalents do not compete for selection. Conclusively, this
model suggests that TOTs can vary with language specificity.
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From these four models, one can conclude that bilinguals should have some amount of TOTs for both
words that they do know and do not know how to translate, and that bilinguals should have more TOTs than
monolinguals regardless of their knowledge of the target word in both languages. Since these bilingual models
assume that the different levels of representation, either semantic, phonological or orthographic, for the two
languages are integrated, identifying where and to what degree these representational levels interact across
languages will shed light on to an understanding of how a bilingual’s production of one language (response
language) can be influenced by the presence of another language not being used (non-response language).
Monolingual models of language processing
Monolingual models of language processing is divided into three main types: those that posit only
forward activation (Gerard & Scarborough, 1989), those that posit cascaded forward activation (Caramazza,
1997; McClelland, 1979), and those that cascade both forward and backward activation (Dell, 1986). Within a
multilevel system of language that comprises semantic, lexical, phonological or orthographic representations,
the flow of activation indicates the transmission of information across different representation levels. For the
forward activation, an activated semantic level may propagate activation to the subsequent lexical or
phonological level, but the reverse process cannot occur. For cascaded forward activation, it precludes backward
propagation as the forward activation does, but it allows the semantic level to propagate activation down to the
lexical or phonological level regardless of completion of its activation. Lastly, the last model that cascades both
forward and backward activation is also called the model of interactive activation, and is proven to be powerful
in accounting for the TOT state in monolinguals and bilinguals.
ERP and fMRI studies of bilingual word production
This paper also looked into scientific methods that elucidate the linguistic theories of selecting and
producing words in both languages for bilinguals. While behavioral methods have been used to examine time
course issues by manipulating task constraints, behavioral approaches are hard to rely on as they inadvertently
obscure response times and the stages of processing. Unlike response time measures, event-related potentials
(ERPs) allow for evaluation of neurocognitive processes with high resolution.
Both empirical studies and ERP results revealed a cognate facilitation effect in both languages,
according to Christoffels et al. (2007). This evidence clearly evinces that cognate words will facilitate word
retrieval than noncognates if translations were phonologically encoded. The node structure theory and TD
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hypothesis approach of the cognate facilitation effect is shown later in the paper.
Previous ERP studies have suggested that both languages are activated when bilinguals intend to
speak only one language. Guo and Peng (2005) used non-cognates in a picture-word interference task, and they
did not obtain significant activation of L1 (mother language) phonology when Chinese-English bilinguals spoke
words in L2 (acquired language). However they reported significant activation of the L1 translation in L2
production. This is another unique study conducted with Western language and Eastern language bilinguals, and
strongly highlights translation as a factor that does contribute to word retrieval facilitation.
fMRI studies also demonstrate language-specific model as the fMRI study conducted by Abutalebi
and Green (2007) claim that there is a single network mediating the representation of a person’s L1 and L2 and
that cortical structure such as LPFC (left prefrontal cortex) and ACC (anterior cingulated cortex) are engaged by
bilinguals to inhibit lexical competition between languages. Another fMRI study by Wang et. al (2007) reported
that both the frontal gyrus and the ACC are involved in language switching, thus suggesting another evidence
for inhibition in bilingual word production. Thus, the fMRI studies evince that there is no direct competition
from the non-target language, which means that the presence of a second language does not hamper the process
of word retrieval in the first language.
Taken together, the evidence from both ERP and fMRI neuroimaging data support a view in which
brain areas associated with inhibitory processing function to aid bilinguals in selecting the language, thus
supporting the language-specific model .
Node Structure Theory Model
The node structure theory (NST) model comes in handy when one investigates the bilingual
representation system. Nodes are the processing units within the memory system which comprise each
independent processing level of language production. The NST model contains vertical and horizontal flows of
information through the semantic, lexical and phonological level. It encompasses cascaded activation with topdown connections between the three levels of processing, a reverse top-down and bottom-up connection, and
sequential left-to-right activation (MacKay, 1987).
All nodes interact within and across processing levels via activation and priming. Activation is an “allor-none” response; in other words, a node is completely activated when it reaches threshold or not at all.
Activation relies on sequence nodes that connect with those in higher and lower levels. Priming, on the other
hand, prepares a node for activation. The node that receives the most priming activates first as it reaches
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threshold quickly.
<Figure 1: Node Structure Theory model (copied from Burke & James, 2000)>
Among the four linguistic models proposed to explain the TOT state, the most influential and
persuasive account has been the Transmission Deficit (TD) hypothesis, which was formulated within the NST
model. The TD hypothesis explains that because of the weak connections among semantic and phonological
nodes, only some of the phonological nodes receive sufficient priming of activation for retrieval. It also
proposes that TOTs can be resolved by additional phonological sources priming the full activation of the target
word’s phonology, which has been demonstrated in various priming studies. (James & Burke, 2000; White &
Abrams, 2002).
For instance, say that a person has a TOT for the word fascism and reports an alternate word facade
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instead. Thereby, the person is essentially reporting the partial phonological component fa. Under the NST and
TD model, the TOT for fascism can be resulted from one of its phonological nodes receiving insufficient topdown priming from the semantic system to be activated (e.g. scism) whereas the other phonological node
received sufficient priming and thus, was activated (e.g. fa). The activated phonological nodes in turn send
bottom-up priming to all lexical and semantic nodes which share those phonological nodes. According to the TD
hypothesis, TOT occurred for fascism by preventing its full activation and retrieval, whereas priming and
activation of fascism resulted in its retrieval with its alternate, façade.
Another way to assist recovery of fascism is through cascaded activation and backward connections.
Say, this time, a person retrieves another alternate word, narcissism, which shares a target phonological
component that is underprimed. This mechanism occurs through additional right-left phonological priming,
which boosts the activation of fa, thereby removing the transmission deficit for fascism and sending feedback to
the lexical level. This process finally allows the correct semantic representation to be retrieved and articulated.
The cross-language interference hypothesis is also valid to account for TOTs in bilinguals when
spoken word production is accomplished with two or more alternatives available. The general assumption in
models of lexical production is that at least three component processes-conceptual level, lemma level,
phonological level-are engaged prior to articulation. A concept and its closest lexical representation must be
selected and the phonology that corresponds to them must be then specified. There can be activation of abstract
candidates at the lemma or phonological level for bilinguals because there are multiple alternatives in each
language, which are prone to be active at any of the loci (Kroll, et. al, 2008). The degree of the sustained activity
of the non-target language depends on a variety of factors, including the target language of production,
proficiency in secondary language, the task that initiates word retrieval, etc. When production occurs in the
mother language, there may be little evidence of influence from secondary language since the mother language
is more skilled than the secondary language in terms of the time course of speech planning. In contrast, when
speech production occurs in the secondary language, there may be multiple influences of the mother language
on the secondary language. Notably, these cross-language interactions function between lexical and sub-lexical
levels but there are two main models that account differently for lexical selection.
First, the language-specific selection model postulates that information about words in the unintended
language may be activated but those non-target words are not candidates themselves for selection (Kroll, et. al,
2008). The presence of cross-language activation itself rules out the possibility of having one of the two
languages switching off or inhibiting in advance to enable the bilingual to function as a monolingual, and recent
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neuroimaging evidence further reinforces this idea, for no brain area is uniquely associated with a language
switch (Wang, Xue, et. Al, 2007). The activated non-target nodes only facilitate the selection of target nodes and
do not compete for selection.
In contrast, the non-specific language model assumes that words in both languages are potential
candidates for selection. Activated nodes in the non-target language compete with the selection of words in the
target language. Evidence for this model says that the non-response language interferes with the target language
(Kroll, et. al, 2008).
Three approaches have been adopted to test the language-specific and language non-specific models
(Colome, 2001). The first approach is to use a variant of the Stroop task, in which pictures are named or words
are translated. A distracter word, which is related to the name of the picture or word to be translated, is
presented visually or auditorily. It is generally predicted that there is no effect of distracters in the non-target
language at the point when one has already decided for language selection.
The second approach involves switching the languages of production to examine the impact of using
alternatives in both languages (Colome, 2001). If both language alternatives are normally active during the
planning of utterance in one language, it is generally predicted that forcing the languages to be mixed disrupts
the mechanism of selection that would ordinarily be adopted under blocked conditions in which languages aren’t
mixed. Therefore, the magnitude of switch cost and its impact on the mother and secondary language can be
examined when bilinguals are required to switch between their two languages.
A third approach to examining language selection processes is to utilize the presence of shared crosslanguage features (Colome, 2001). It is possible to have bilinguals perform a task in one language alone and to
ask whether their performance in producing words with shared-language features is similar to words that are
unique to one language because many languages share aspects of their lexical or sub-lexical representations. If
both languages are active when a single language is required to be produced, these language ambiguous
materials would give rise to a different pattern of performance than a language unique material would. In
addition, bilinguals and monolinguals are likely to perform similarly on language unique words but only
bilinguals are expected to respond differently to the language ambiguous words (Kroll, et. al, 2008).
Summarizing, this comparison of the effects for language pairs with different properties gives insight into
whether language selection is sensitive to language-specific features. (*E.g. lang-unique, lang-amb words!!!)
Not only do studies on monolingual language production, cognition, and memory validate the NST as
a reliable and accurate model of language processing but also does the specific speculation of bilingual language
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processing shows potential to accommodate the model’s complexity. To further assess the accuracy of NST
models on bilingual systems, cognate effects and translatability effects need to be looked into.
The Cognate Effect
Cognates are words whose translations have similar phonological and/or orthographic properties. For
instance, “cavall” (Catalan) and “caballo” (Spanish) are similar phonologically and both mean “horse”. On the
other hand, noncognate translations only share their meaning and not in their phonological origins. For example,
“taula” (Catalan) and “mesa” (Spanish) are noncognate words that both mean table. Costa, Caramazza, and
Sebastian-Galles (2000) evinced that if translations were phonologically encoded, cognate words will facilitate
retrieval than noncognates, providing two reasons for support. First, common phonemes for the target word and
its cognate translation receive extra activation, facilitating easier retrieval. Second, the noncognate words, which
have their phonemes of their translation activated, would cause interference. Conclusively, bilinguals needed
less time to produce cognates than noncognates, while no differences were found in monolingual controls.
Gollan and Acenas (2004) hypothesized that insufficient priming of phonological nodes causes TOTs,
and additional priming of these nodes from other sources can resolve TOTs. They studied TOTs for cognate and
non-cognate picture names in Spanish-English bilinguals, Tagalog-English bilinguals, and age- and educationmatched monolingual control groups. Their crucial finding suggests that, relative to frequency-matched noncognates, bilinguals had fewer TOTs for cognates that they could translate while monolinguals did not show
cognate effects. In other words, Gollan and Acenas suggest that TOTs are reduced when a word such as
rhinoceros is translated as rinoceronte but is likely to cause TOTs when it is translated as its non-cognate
counterpart tweezers. Furthermore, another remarkable finding in their study is that bilinguals did not report
more TOTs than did monolinguals only when the pictures of the experiment had translatable cognate names, but
in other cases, bilinguals consistently reported more TOTs than monolinguals. This was a novel discovery since
bilinguals had been known to experience more TOTs than monolinguals (Emmorey, et. al, 2009). From this
result, Gollan and Acenas (2004) could confirm the TD hypothesis, as they said their experiment proved “the
only existing TOT account that predicted cognate facilitation effects” (p.262).
The cognate effect of TOTs supports the TD hypothesis, and thus the bilingual applicability of the
NST model, as it shows that priming of phonological nodes reduces transmission deficit across phonological
connections and helps prevent TOTs. Conclusively, the cognate effect suggests the sharing of phonological
nodes, which indicates that phonological representations are integrated between the two languages of a bilingual.
Therefore, from the cognate effect perspective, the NST model is a useful framework for language
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representation and processes in bilingualism. Because the NST model underlies interactive activation, bilingual
models assume that each language is comprised of four representational levels (semantic, lexical, phonological,
and orthographic). Most bilingual models also assume that these levels are integrated across languages.
The Translatability Effect
The cross-language interference hypothesis predicts that bilinguals should have more TOTs for words
that they can translate relative to words they cannot translate, and more TOTs than monolinguals only when
they can produce the translation equivalent of a TOT target. Gollan and Acenas (2004) tested translatability
effects on Spanish-English and Tagalog-English bilinguals, and they concluded that bilinguals still had more
TOTs than did monolinguals for the translatability matched set of noncognate targets. Furthermore, bilinguals
had fewer TOTs for noncognates that most bilinguals could translate.
Some bilingual experiments also use the picture-word interference task, which requires participants to
name the picture in one language while ignoring the superimposed distracter words given in the second
language. These experiments may give insight into the influence of the non-response language on the response
language. Costa et al. (1999) investigated a “through translation effect” by measuring the time it took CatalanSpanish bilinguals to name pictures. When the Catalan-Spanish bilinguals (first language (L1) Catalan, second
language (L2) Spanish) to name pictures in which their distracters were phonologically related to the picture via
translation. Both experiments were compared to a control group which its distracter’s translation was not
phonologically related to the picture. As a result, Costa et. al (1999) did not find phonological facilitation
through translation, which bolsters the language-nonspecific model. On the other hand, Hermans (2004)
predicted that distracters that are also the names of other pictures will strengthen the translation activation. His
study on Dutch-English bilinguals showed that they could name pictures in their second language (English)
faster when the first language (Dutch) distracters were names of other pictures and whose second language
(English) translations were phonologically related to the second language (English) picture. In contrast with the
study conducted by Costa et. al (1999), Hermans’(2004) study provides evidence for the language-specific
model. Hence, the two studies that use the “through translation effect” does not reach a definite conclusion,
although they do have potential to identify the contribution of phonological effects on bilingual language
selection.
These two previous studies, however, are limited to show the translation effect by evaluating the
participants’ conscious awareness of the translated distracter words. This limitation provided the motivation for
a modification in the experiment. Thus, this paper aimed to evaluate the participants’ recognition of the
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translated equivalent and how the recognition was processed unconsciously in their minds throughout the
experiment. Through my original experiment, I tried to question pose two questions. First, do Korean-English
bilinguals fail to retrieve words from each language differently than previous research conducted on SpanishEnglish, and Farsi-English bilinguals? Second, is translation a factor that facilitates or inhibits the process of
word retrieval? Two hypotheses were made, in accordance with the language-specific selection and the
transmission deficit model. First, it was predicted that Korean-English bilinguals will fail to retrieve words
differently from Spanish-English and Farsi-English bilinguals because they speak in two languages in which the
translation equivalents have no phonological nor orthographic similarity. Second, it was predicted that knowing
the translation of a word will not inhibit the process for retrieving it under time pressure. Although Korean and
English have different alphabet systems and linguistic rules on word formation, the dominant theory of the
language-specific selection argues that activated non-target nodes do not compete for selection.
Original Research
Method
Participants
Participants were 20 Korean-English bilinguals (M age=19.05) who volunteered to join the
experiment. The 20 participants were native speakers of Korean (L1) who learned English (L2) as a second
language at a young age (M age =5.65). Self-reported fluency on a 5-point scale showed a mean of 3.99 for
Korean and a mean of 3.85 for English, which indicates that this group of bilinguals was equally and highly
proficient in both languages. Self-reported official education in each language showed a mean of 11.9 years for
Korean and a mean of 11.35 years for English.
Mean
Years of
official
edu. in
KR
11.9
Years of
official
edu. in
EN
11.35
Age of
first
exposure
to KR
1.1
Age of
first
exposure
to EN
5.65
Self-rated
KR
proficiency
Self-rated
EN
proficiency
Years
lived in
Korea
3.99
3.85
16
Years lived
in a ENenvironment
country
2.34
Materials
Twenty Korean target words were selected from two TOKL (Test of Korean Language) prep books
tailored to high school students in Korea, and twenty English target words were selected from Barron’s SAT. The
definition of the target words and the first letters of each word were presented in a PowerPoint presentation. A
list of 20 Korean-translated words of the previous English target words and 20 English-translated words of the
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previous Korean target words was prepared to assess the unconscious translation effect.
Procedure
Participants were given 30 seconds to retrieve the target word. If the participant could not retrieve the
word during the 30 second interval, he or she reported how they tried to process the word in order to correctly
assess their TOT state (see below for details). In addition, participants had 3 seconds before the next word to
clear distracting thoughts and to focus on the experiment. After going through 20 English words and 20 Korean
words, the participants were given a list of 20 Korean-translated words of the previous English target words and
20 English-translated words of the previous Korean targets words. The participants were told to mark each
translated word that they feel related to the words from the PowerPoint.
Before the test, the participants were given a language proficiency questionnaire to assure their equal
fluency in both languages. The definition of the TOT state was explained to the participants beforehand, and
they were also told that they can report certain physical characteristics of the word when they are in a TOT state.
They were also told that the TOT state has 7 categories (GOT, +TOT, -TOT, pre-DK, target unclear, recognize,
post-DK). GOT was scored when the participant was able to retrieve the target word within 10 seconds. +TOT
was scored if the participant retrieved the target word between 10 to 30 seconds and reported having feelings of
a TOT state. –TOT was scored if the participant could not retrieve the word in 30 seconds, but was close to
saying the target word and could have retrieved it if they were given more time, or it was also scored if the
participant retrieved a synonym instead of the actual target word and reported feelings of a TOT state. Pre-DK
was scored if the participant reported feeling certain that she or he would not know the word after hearing it.
Target unclear was scored if the participant is not in a TOT state but guessed a synonym. Recognize was scored
if the participant reported knowing the target word after it was presented, and post-DK was scored if the
participant reported not recognizing the target word after it was presented.
Hypothesis
For the experiment, it is expected that knowing the translation of a word will inhibit the process for
retrieving it under time pressure because Korean and English have different alphabet systems and linguistic
rules on word formation. Korean-English bilinguals are unique from previous research in that they speak in two
languages in which the translation equivalents have no phonological nor orthographic similarity. Comparing the
frequency of TOT rates in Korean-English bilinguals with those of Spanish-English1, Tagalog-English1, and
Farsi-English2 bilinguals published in other papers will provide a better understanding of how different
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languages and word structure influence TOT rates, and shed light on the nature of the representational system in
bilinguals.
Results
The following data table displays the mean and standard error of means (SEM) value of the main three
categories that are analyzed in this paper. YTL indicates that the participant was cognizant of the translation
equivalent and NTL indicates that the participant was not aware of the translation equivalent during the study.
GOT (EN)
GOT (KR)
+TOT(EN)
+TOT(KR)
-TOT(EN)
-TOT(KR)
Mean
5.3
7.1
1
1.2
1.75
1.75
SEM
0.6732
0.6444
0.2616
0.2956
0.3315
0.3067
YTL
GOT
(EN)
NTL
GOT
(EN)
YTL
GOT
(KR)
NTL
GOT
(KR)
YTL
+TOT
(EN)
NTL
+TOT
(EN)
YTL
+TOT
(KR)
NTL
+TOT
(KR)
Mean
4.8
0.5
6
11
0.75
0.25
0.75
0.4
SEM
0.6513
0.1701
0.6198
0.2606
0.2280
0.1230
0.25
0.1338
Mean
YTL
-TOT (EN)
1.35
NTL
-TOT (EN)
0.4
YTL
-TOT (KR)
1.35
NTL
-TOT(KR)
0.4
SEM
0.3267
0.1522
0.2927
0.1124
The following are charts of each categories (GOT, +TOT, -TOT) in which their frequencies were analyzed
based on the knowledge of translation equivalents.
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1.2
1
0.8
0.6
0.4
0.2
0
YTL +TOT (KR)
NTL +TOT (KR)
YTL +TOT (EN)
NTL +TOT (EN)
1.2
1
0.8
0.6
0.4
0.2
0
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
YTL -TOT (EN)
NTL -TOT (EN)
15
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
YTL -TOT (KR)
NTL -TOT (KR)
Since the participants in two groups are identical, a paired t-test was conducted to compare the frequency of
each TOT category and its dependence on prior knowledge of translation. With the exception of one case
(+TOT), the other categories failed the normality test, so a signed ranked test, which is a statistical test that
evaluates non-parametric methods, was conducted to compare the frequency of each categories in TOT with
respect to prior knowledge of translation. According to the paired t-test, significant difference between two
groups increases as the p-value decreases. (*p < 0.05, **p < 0.01, ***p < 0.001) GOT category for both English
and Korean had a p-value of lower than 0.001. +TOT category for English had a p-value of 0.077, which
indicates an insignificant value. +TOT category for Korean had a p-value of 0.297, which also indicates an
insignificant value. –TOT category for English had a p-value of 0.021, which is a quite significant outcome. –
TOT for Korean passed the normality test, thus a two-tailed paired t-test was conducted. Its p-value is 0.008,
which indicates a significant value.
Discussion
The primary goal of the present study was to demonstrate that translation is a factor that
unconsciously influences word retrieval, and showed that prior knowledge of translation does affect the
frequency of -TOTs significantly. The results of the experiment satisfy this goal. The translation effect was
demonstrated strongly in the GOT and –TOT category but not as much in the +TOT category. The first
hypothesis was confirmed: participants reported similar frequency rates in both English and Korean, especially
for the statistically significant –TOT values. The result for GOT showed that participants reported a higher
frequency of GOT. The mean frequency of –TOT was relatively higher than the mean frequency of +TOT. The
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participants generally reported a higher frequency in GOT, which indicates that it was easier for them to recall
certain words in their native language than in their second language. The second hypothesis was also confirmed:
participants had a higher TOT frequency (both +TOT and –TOT) when they had prior knowledge in the
translation equivalents. Moreover, prior knowledge of translation rather functioned to inhibit word retrieval than
to facilitate word retrieval because the mean frequency of TOTs with YTL(knowledge of translation) were
greater than the mean frequency of TOTs with NTL (no knowledge of translation). This paper interpreted GOTs
and +TOTs as facilitation of word retrieval and –TOTs as inhibition of word retrieval. From this perspective, the
mean frequency of –TOTs with and without knowledge of translation were greater than that of +TOT, which
signals that translation did significantly inhibit the process of quick word retrieval.
COMPARISON WITH SPANISH, TAGALOG, FARSI BILINGUALS.
It is important to note that only tentative conclusions can be drawn from the data, especially for the
+TOT data, until more participants are tested. Disregarding the ‘recognize’, ‘post-DK’ and ‘pre-DK’ from the
experiment, -TOT had a mean frequency of 1.75 for English (p<0.021) and 1.75 for Korean (p<0.008). This fact
suggests that the –TOT’s influence on word retrieval is significant. On the other hand, further testing is
necessary to disambiguate the marginally significant trend of +TOTs for English (p=0.077) and for Korean
(p=0.297).
This finding suggests that translational priming inhibited TOTs by causing interference between
phonological and semantic connections, thereby hindering correct retrieval. This result would be in line with the
account of language-nonspecific selection, which predicts interference from the nonresponse language on
response language. Evidence from the experiment conducted with Korean-English bilinguals demonstrates that
the nonresponse language interferes with the response language. This postulates that all activated words, target,
or nontarget, and their activated feature nodes are candidates for selection. Accordingly, activated nodes in the
nonresponse language compete with the selection of words in the response language. The experimental result
supports the TD hypothesis because it explains TOT as a consequence of insufficient transmission of activation
from the semantic level to the phonological level. The selected words in the experiment did not contain
phonologically similar words in Korean and in their English counterparts. For instance, “hedonist” was one of
the answers of the experiment. Its single Korean translation counterpart is “querak-jueuija” (쾌락주의자).
Apparently viewed from both phonological and orthographic levels, there is no critical overlap of neither levels.
17
It is also possible that the results could have been skewed if the participants happened to have lower
vocabulary in English than in Korean. This might account for their increased post-don’t know responses in
English. However, the present study only asked for self-assessment of each language and not the participants’
vocabulary. Therefore, this possibility
18
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