Behavior Research Methods, Instruments. & Computers 1999.31 (4). 650-658
Naming times für the Snodgrass and Vanderwart pictures in Spanish FERNANDO CUETOS
University ojOviedo, Oviedo, Spain ANDREW W. ELUS
University oj York, York, England and BERNARDO ALVAREZ
University ojOviedo, Oviedo, Spain We present new Spanish nonns for object familiarity and rated age of acquisition for 140 pictures taken from Snodgrass and Vanderwart (1980), together with data on visual complexity, Image agreement, name agreement, word length (in syllables and phonemes), and five measures of ward frequency. The pictures were presented to a group of 64 Spanish subjects, and oral naming latencies were recorded. In a multiple regression analysis, age of acquisition, object familiarity, name agreement, ward frequency, and ward length made significant independent contributions to predicting naming latency. In recent years, numerous papers have been published analyzing the properties of objects and their names that influence picture-naming speed. The findings of such studies are impartant in the development of cognitive models of object recognition and naming. Many ofthese studies have used a set of 260 black-and-white line drawings of objects published by Snodgrass and Vanderwart (1980) with American norms for visual complexity, object familiarity, image agreement, and name agreement. One of the factors that has proven consistently to be a powerful predictor of naming speed is age of acquisition, a measure ofthe age at which children first learn the names of different objects. Many of the studies have relied on adult estimates of age of acquisition (e.g., Carroll & White, 1973; Gilhooly & Gilhooly, 1979; Morrison, EIlis, & Quinlan, 1992), but Morrison, ChappeIl, and Ellis (1997) derived objective age-of-acquisition norms from children's object-naming data and showed that there was good agreement between objective and rated measures. Ellis and Morrison (1998) found that objective age of acquisition was a strong predictar of adult object-naming speed in their own data and also in data from Barry, Morrison, and Ellis (1997) and Snodgrass and Yuditsky (1996). The frequency with which words are used and encountered is another factor that exerts a clear influence on naming speed. Although some studies offrequency effects in object naming could be criticized for failing to control for This research was supported by Grant DGE-96-PB-0545 from the Spanish government. We thank Joan Snodgrass and Frances Connors for helpful comments on an earlier version of this article. Correspondence concerning this article should be addressed to F.Cuetos, Departamento de Psicologia, Universidad de Oviedo, Plaza Feijoo s/n, 33003 Oviedo, Spain (e-mail:
[email protected]).
Copyright 1999 Psychonomic Society, Inc.
differences in age of acquisition (Ellis & Morrison, 1998), an effect of frequency continues to be found when age of acquisition is controlled (Barry et al. , 1997; Ellis & Morrison, 1998; Snodgrass & Yuditsky, 1996). Another factor to emerge with reasonable consistency as a predictor of naming speed is name agreement, measured as the proportion of speakers who assign the target name to a given object. If an object has more than one plausible, alternative name (e.g., gun/pistol/revolver), the retrieval of any one of those names appears to be slowed, possibly because the target name must compete with the alternatives for selection (Vitkovitch & TyrreIl, 1995). All of the above-mentioned studies have involved naming in English. Work in other languages on the factors affecting object-naming speed is limited to a small number of studies in languages such as Dutch (e.g., Jescheniak & Levelt, 1994) and French (e.g., Bachoud-Levi, Dupoux, Cohen, & Mehler, 1998). If models of object recognition and naming are to have universal application, it is important that comparative data be obtained from a wider range of languages. The present paper reports a study in which 64 Spanish participants named 140 pictures taken from the Snodgrass and Vanderwart (1980) set. All the objects had single-word names in Spanish. New norms were obtained for age of acquisition in Spanish for use in the analysis. New norms were also obtained for object familiarity, because of the possibility of crosscultural differences in the familiarity of different objects and because, although Sanfeliu and Fernandez (1996) have published familiarity ratings, some common, everyday objects have surprisingly low familiarity ratings in those norms (e.g., glass, 2.35; chair, 2.10; scissors, 1.43; on a 5-point scale from 1 = unfamiliar to 5 = highly familiar), whereas less frequently encountered objects
650
PICTURE NAMING IN SPANISH have much higher ratings (e.g., rhinoceros, 4.73; tiger, 3.24; snake, 3.82). Adult word frequencies were taken from the frequency dictionary of Alameda and Cuetos (1995). Measures ofthe frequency with which children use different object names were also taken from data published by the Spanish Ministry ofEducation (MEC, 1989) and the Institute ofEducation (ICE, 1977). Finally, measures of visual complexity, image agreement, and name agreement were taken from Sanfeliu and Fernandez (1996). METHon Stimuli The stimuli were 140 black-and-white line drawings of objects taken from the set of 260 published by Snodgrass and Vanderwart (1980). The selected objects all had single-word names in Spanish, with name agreements of over 84% (Sanfeliu & Fernandez, 1996) and with ratings for name agreement, visual complexity, and image agreement being available from Sanfeliu and Fernandez. (Name agreement refers to the percentage of speakers who assign the target name to a given picture, visual complexity is arated measure of the complexity ofthe line drawing, and image agreement is a measure ofthe extent to which the drawing matches the visual image of an object that a person forms on being given the object name.) Ratings of object familiarity were collected by following the Barry et al. (1997) procedure. Raters were given eight booklets. The first booklet contained the written instructions, which specified that they were to judge the familiarity of each object they would see on a 5-point scale from I (ve,:y untamiliari to 5 (highlyfamiliar). Familiarity was defined as "the degree to which you come in contact with, or think about, the thing depicted." The remaining seven booklets each contained 20 Snodgrass and Vanderwart pictures to be rated. The subjects worked through the booklets in a random order. The raters were 93 first-year psychology students from the University ofOviedo. The age-of-acquisition ratings were obtained from a sampie of 50 students from the University of Oviedo, who were asked to give an estimate of the age at which they believed they had learned each word. The scale on which they had to indicate the acquisition age ranged from I to 11, where I = before 2 years old, 2 = two years old, 3 = three years old, and so on, up to 11 = eleven years old or older. Adult word frequencies (fAC) were taken from Alameda and Cuetos's (1995) dictionary ofword frequencies, which is based on a corpus ofwritten texts comprising 2 million words. Three further frequency measures were obtained. These are based on studies carried out with Spanish children and published by the Spanish Institute ofEducation (ICE, 1977) and the Ministry ofEducation (MEC, 1989). ICE is a written production frequency measure compiled from 3,150 children ranging in age from 8 to 17 years, with 630 children in each ofthe age groups 8-9,10-11, 12-14, 15-16, and 17 years of age. The children were simply instructed to write down all the words they could think of in the space of 5 min (10 for the youngest), not just object names. A total of 9,782 different words were collected. The MEC (1989) written production frequency measures were developed by the Spanish Ministry ofEducation, with 8,714 pupils, 6-14 years of age, drawn from every region ofSpain. A spontaneous frequency measure (MECsp) followed a procedure similar to that of the ICE frequency: The children had to write down all the words they could think ofin the space of 10 min (for the younger ones) or 5 min (for the older children). The suggested frequency measure (MECsu) used a similar proccdure, except that a theme was given and the children were asked to give words related to the theme. Sixty different themes were used. A total of 18,881 different words were
651
collected, using the two procedures. The total frequency measure (MECto) is simply the sum ofthe two previous ones. Other variables were the numbers of syllables and phonemes in the spoken Spanish object name.
Subjects and Procedure The subjects were 64 undergraduate students of psychology at the University ofOviedo. All were monolingual Spanish speakers, and all participated voluntarily in the experiment. None had participated in the rating exercises. The experiment was controlled by using the ERTS experimental program (Beringer, 1995). The pictures were presented in the center of a computer screen. The subjects remained seated in front of the screen, with a microphone, held in place by headphones, in front of their mouths that was connected to a voice key. When the picture appeared, the computer chronometer was started, and when the subject gave a response, the chronometer was stopped, and the cornputer automatically recorded the time elapsed. The picture disappeared from the screen as soon as there was a response, and in its place, a cross appeared in the center ofthe screen, serving as a fixation point and staying in for 2,000 msec. After this time, the fixation point disappeared, and a new picture appeared. The maximum time a picture stayed on the screen was 4,000 msec. If, after this time, the subject had given no reply, the picture was replaced by the fixation point, and an error was recorded. Before the start ofthe experiment, the voice key was adjusted to suit each subject's sensitivity, and six trial items were presented. The instructions were given, basically consisting of an explanation ofthe experiment and a warning not to move their heads too much, not to cough or breathe loudly, and not to say anything other than the picture names. After the instructions had been given, the first set of stimuli, consisting of 6 practice trials and 70 experimental trials, was presented. After this, there was a short rest; then, the second set was presented, again consisting of 6 practice and 70 experimental pictures. The experiment stimuli were randomized for each subject. Simultaneously with the start of the experirnent, a recorder was set running for the later analysis of incorrect responses given by each subject.
RESULTS Before calculating the means of the reaction times (RTs), we eliminated those items for which the subjects had given an incorrect response or had triggered the voice key by coughing or moving their heads. There were only 3.28% incorrect responses and 3.53% voice key failures. Following the procedure adopted by Snodgrass and Yuditsky (1996), scores Iying more than two standard deviations from the mean were removed, in order to eliminate the influence of outliers. This resulted in the removal of 4.14% of responses. The mean ofthe naming times was then calculated for each item. The mean naming speeds for each item are shown in the Appendix, along with the percentage of errors made to each item in the present study, plus the values for each item on the different predictor variables. The global mean naming latency for the 140 items was 829 msec, somewhat slower than the RTs obtained by Barry et al. (1997) with Welsh subjects (748 msec), by EIlis and Morrison (1998) with English subjects (794 msec), and by Snodgrass and Yuditsky (1996) with American subjects (791 msec). The correlations of each predictor variable with naming RT and the significant correlations between the 12 pre-
652
CUETOS, ELLIS, AND ALVAREZ
dictor variables are shown in Table I. The frequency measures were all transformed, using the formula log(l + x) to reduce skew. As in many of the studies mentioned in the introduction, the predictor variable that has the highest simple correlation with naming speed is age of acquisition. Naming time also correlates significantly with object familiarity, name agreement, word length, and each ofthe frequency measures. There are also, however, significant correlations between some of the predictor variables, meaning that the correlations with naming speed must be interpreted with caution. For example, familiarity correlates with age of acquisition (the more familiar pictures have names that are acquired at an early age) and with frequency (the more familiar pictures have more commonly occurring names), whereas word length correlates with age of acquisition (Iater acquired words tend to be longer) and word frequency (Iess frequent words tend to be shorter).
Stepwise Multiple Regression A stepwise multiple regression was carried out on the naming RTs, using all 12 predictor variables. Age of acquisition was the first variable to be entered (ß = .52, t = 7.1O,p < .0001), followed by Alameda and Cuetos's (1995) word frequency (ß = - .27, t = - 3.53,p < .001), percentage ofname agreement (ß = -.16, t = -2.26, p < .05), object familiarity (ß = - .20, t = -2.23, p < .05), number ofsyllables (ß = .15, t = 2.l4,p < .05), and image agreement (ß = - .14, t = -2.00, p < .05). Multiple R for these six factors was .65, which was highly significant (F = 15.68,p< .001). None ofthe remaining factors were significant sources ofvariance. Simultaneous Multiple Regressions Stepwise regressions can be problematic when the predictor variables are themselves intercorrelated (Morris, 1981). Here, for example, five different frequency measures were entered into the stepwise regression analysis, one ofwhich (MECto) is the simple sum oftwo ofthe
others (MECsu and MECsp). To confirm and strengthen the findings of the stepwise analysis, a set of simultaneous multiple regression analyses were also carried out. These analyses all had age ofacquisition, visual complexity, object familiarity, image agreement, and percentage ofname agreement as predictor variables, plus one ofthe five frequency measures (fAC, ICE, MECsp, MECsu, or MECto) and one of the two length measures (syllables or phonemes). As before, the frequency measures were transformed using the formula log(l + x). Table 2 shows the results ofthe analysis with Alameda and Cuetos's (1995) fAC as the frequency measure and number of syllables as the length measure. The overall regression equation was significant [F(7,131) = 13.38, p< .001, R = .646]. Taken together, the predictor variables accounted for 42% ofthe variance. The results are very similar to those ofthe stepwise regression analysis, with age of acquisition, word frequency, name agreement, object familiarity, number of syllabIes, and image agreement all making independent contributions toward predicting naming speed. As before, the effect of visual complexity was not significant. Age ofacquisition, name agreement, and object familiarity were significant in all the other simultaneous regressions with number of syllables or number of phonemes as the length measures. With number of phonemes, Alameda and Cuetos's (1995) fAC was again significant. None of the other frequency measures (ICE, MECsp, MECsu, or MECto) made a significant independent contribution, whether combined with number of syllables or number ofphonemes as the length measure.
DISCUSSION The variable that showed the highest raw correlation with naming RT was age of acquisition. It also proved to be significant in all of the regression analyses. This is very much in line with the findings of studies of naming in English, where age of acquisition is the one factor that has emerged as a significant predictor in every study that
Table 1 Correlation Matrix Among All the Independent Variables and Naming Reaction Time Variable
(I)
(2)
1. Naming RT 2. AoA 3. Visual complexity 4. Familiarity 5. Image agreement 6. No. phonemes 7. No. syllables 8. % Name Agreement 9. Log (I + fAC) 10. Log (I + ICE) 11. Log (I + MECsp) 12.Log(l+MECsu) 13. Log (I t MECto)
1.000 .519*
1.000
- .474*
- .585*
.229* .292* - .253* - .427* -.462* - .373* -.397* -.384*
.231t .212t - .190t - .384* -.612* -.492* -.548* -.514*
(3)
(4)
1.000 -.353*
1.000
(5)
(6)
(7)
1.000 .863*
1.000
- .297* -.213t
- .303* -.264t
(8)
(9)
(10)
(11)
(12)
(13)
1.000 -.202t - .222t
.486* .622* .429* .519* .459*
.259* - .219t -.194t
1.000 1.000 .592* 1.000 .670* 1.000 .442* .713* .888* .418* .692* .993*
1.000 .936* 1.000
Note-AoA, age-of-acquisition rating; fAC, adult word frequency; ICE, frequency for children from Institute of Education; MECsp, Ministry of Education spontaneous frequency measure; MECsu. Ministry ofEducation suggested frequency measure; MECto, Ministry ofEducation total frequency measure. *p< .001. tp < .01. tp< .05. A dash indicates that the correlation was not significant.
PICTURE NAMING IN SPANISH
'!'-
Table 2 Simultaneous Multiple Regression Analysis on the Picture Naming Reaction Times Variable
Mean
SD
Visual complexity 2.56 .88 Object familiarity 3.24 1.07 Image agreement 3.75 .58 % name agreement 96.16 4.08 AoA 4.21 .71 Log (I +fAC) 1.55 .62 No. of syllables 2.51.73
653
ßCoefficient
SE
t Value
-4.31 -22.60 -27.93 -3.98 39.16 -37.46 24.05
9.94 9.47 133.68 1.89 13.23 15.15 10.48
-0.47 -2.38t -2.04t -2.llt 2.96* -2.47* 2.30*
Note-AoA, age-of-acquisition rating; fAC, adult word frequency. *p< .01. t p < .05.
has inelud~d it (s.ee Ellis & Morrison, 1998). The present .stu~y ISthe first to extend that observation to object nammg in other languages. Some previous studies ofnaming in English have failed to observe an effect ofword frequency on naming speed, once age of acquisition is controlled statistically (e.g., ~arroll & White, 1973; Gilhooly & Gilhooly, 1979; Mornson et al., 1992), but more recent studies involving larger numbers of items have typically found an influence of frequency over and above the effect of age of acquisition (Barry et al., 1997; Ellis & Morrison, 1998; Snodgrass & Yuditsky, 1996). In the present study, the frequency measure based on adult language sampies (fAC) made a ~ignifican~ independent contribution to predicting nammg speed m the stepwise multiple regression and in both of the simultaneous regression analyses in which it was ineluded. None of the frequency measures based on child .Ian~uage sampies made a significant independent contribution to predicting naming speed. Thus, it may be that, once age of acquisition is accounted for, the most rel~vant measure ofword frequency is the frequency with which adults encounter or use different words in daily life. Object familiarity, image agreement, and name agreerr:ten~ :-vere the other factors to emerge consistently as ~lg!llflcant determinants ofnaming speed. Object familianty was significant in certain of the analyses reported by Ellis and Morrison (1998). It might be thought of as the perceptual equivalent of word frequency: The more often an object is encountered (i.e., the more familiar it is), the more easily it is recognized for what it is. Two recent studies of patients with semantic dementia have reported effects of familiarity on object naming and have a.rgued ~hat familiarity influences the ability ofthese patients either to recognize the objects as familiar or to access their semantic representations (Hirsh & Funnell, 1995; Ralp?, Graham, Ellis, & Hodges, 1998). Image agreement IS the extent to which a picture matches the mental image of an object and might be thought of as a measure of the match or mismatch between the picture and a stored canonical representation ofthe object's appearance. The eloser the image is to the representation the more quickly it can be recognized. ' Effects of name agreement have been reported in a number of previous studies (e.g., Lachman, Shaffer & Hennrikus, 1974; Snodgrass & Yuditsky, 1996; Vitko-
Tyrrell, 1995). The usual assumption is that, if vitch an o?Je~t can be given more than one plausible name, nammg ISslowed by the need to select between them. Fin~lly, ~ord le~gth has tended not to be a significant predictor In studies of English naming, but was so here, when mea.sured in terms ofthe number of syllabies. It may b.e that this relates to the fact that Spanish is a syllabletimed language, whereas English is stress-timed, but it rnay also be that Spanish object names cover a wider range of syllable lengths in a more even manner, making an effect of length easier to detect. Picture ~aming may be thought ofas involving aseries of~rocessIng stages, one ofwhich involves recognizing the Image as a representation ofa familiar object. We have suggested that effects of familiarity and image agreement operate at this stage. A subsequent stage involves acc.essing the ~poken name. Contemporary models of lexical processmg suggest that the more often a word is activated, the stronger become the connections between it and o~her representat!ons, ineluding the semantic representations used to activate the word (e.g., lescheniak & Levelt, 1994). We would suggest that the fAC effect picks up on those differences in connection strengths. Brown and Watson (1987) proposed that early-acquired words may.have more unitary, localized phonological representations, whereas the representations of lateracquired words may be more distributed. They suggested that the extra processing time incurred in assembling the fragmented representation of a late-acquired word would ~ccount fo~ the additional time required for object nammg or readmg aloud (cf. Morrison & Ellis, 1995). Whatever the merits of this particular proposal, the present data are certainly compatible with the hypothesis that age of acquisition affects the speed of accessing or retrieving phonological word forms. The effect of number of syllables obtained here, if reliable (cf. Bachoud-Levi et al., 1998), might indicate that longer words take longer to assemble or that more time is required to initiate their articulation. . Perhaps t?e most encouraging thing for those engaged ~n the creation of models of lexical processing that are mtended to be universal in their application is the fact that the findings of the present study of object naming in the Spanish language are in such elose agreement with the findings of the many previous studies involving speakers of English. REFERENCES ALAMEDA, J. R., & CUETOS, F. (1995). Diccionario de frecuencias de las unidades linguisticas dei castellano. Oviedo: Servicio de Publicaciones de la Universidad de Oviedo. BACHOUD~LEVI, A. C., Duroux, E., COHEN, L., & MEHLER, J. (1998). Where IS the length effect? A cross-linguistic study of speech production. Journal 0/ Memory & Language, 39, 331-346. BARRY, c., MORRISON, C. M., & ELLlS, A. W. (1997). Naming the Snodgrass and Vanderwart pictures: Effects of age of acquisition, frequency and name agreement. Quarterly Journal of Experimental Psychology, 50A, 560-585. BERINGER, J. (1995). Experimental run time system. Frankfurt: BeriSoft.
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BROWN, G. D. A., & WATSON, F. L. (1987). First in, first out: Word learning age and spoken word frequency as predictors ofword familiarity and word naming latency. Memory & Cognition, 15, 208-216. CARROLL, J. B., & WHITE, M. N. (1973). Word frequency and age-ofacquisition as determiners ofpicture-naming latency. QuarterlyJournal 0/ Experimental Psychology, 25, 85-95. ELLIS, A. W, & MORRISON, C. M. (1998). Real age of acquisition effects in lexical retrieval. Journal 0/ Experimental Psychology: Learning, Memory, & Cognition, 24, 515-523. GILHOOLY, K. J., & GILHOOLY, M. L. (1979). Age-of-acquisition effects in lexical and episodic memory tasks. Memory & Cognition, 7, 214-223. HIRSH, K. W, & FUNNELL, E. (1995). Those old, familiar things: Age of acquisition, familiarity and lexical access in progressive aphasia. Journal ofNeurolinguistics, 9, 23-32. ICE (1977). Vocabulario basico dei espaiiol y sus aplicaciones a la enseiianza. Oviedo: Instituto de Ciencias de la Educaciön, JESCHENIAK, J. D., & LEVELT, W J. M. (1994). Word frequency effects in speech production: Retrieval of syntactic information and ofphonological form. Journal 0/ Experimental Psychology: Learning, Memory. & Cognition, 20, 824-843. LACHMAN, R., SHAFFER, J. P., & HENNRIKUS, D. (1974). Language and cognition: Effects of stimulus codability, name-word frequency, and age of acquisition on lexical reaction time. Journal 0/ Verbal Learning & Verbal Behavior, 13,613-625. MEC (1989). Vocabulario basico en la E.G.B. Madrid: Ministerio de Educacion y Ciencia and Editorial Espasa Calpe. MORRIS, P. E. (1981). Age of acquisition, imagery, recall, and the limitations ofmultiple-regression analysis. Memory & Cognition, 9, 277-282.
MORRISON, C. M., CHAPPELL, T. D., & ELLIS, A. W (1997). Age of acquisition norms for a large set of object names and their relation to adult estimates and other variables. Quarterly Journal 0/ Experimental Psychology, 50A, 528-559. MORRISON, C. M., & ELLIS, A. W. (1995). The roles ofword frequency and age of acquisition in word naming and lexical decision. Journal 0/ Experimental Psychology: Learning, Memory. & Cognition, 21, 116-133. MORRISON, C. M., ELLIS, A. W, & QUINLAN, P. T. (1992). Age of acquisition, not word frequency, affects object naming, not object recognition. Memory & Cognition, 20, 705-714. RALPH, M. A. L., GRAHAM, K. S., ELLIS, A. W, & HODGEs,J. R. (1998). Naming in semantic dementia-what matters'? Neuropsychologia, 36, 775-784. SANFELIU, M. C, & FERNANDEZ, A. (1996). A set of 254 SnodgrassVanderwart pictures standardized for Spanish: Norms for name agreement, image agreement, familiarity, and visual complexity. Behavior Research Methods, Instruments, & Computers, 28, 537-555. SNODGRASS, J. G., & VANDERWART, M. (1980). A standardized set of 260 pictures: Norms for name agreement, image agreement, familiarity, and visual complexity. Journal 0/ Experimental Psychology: Human Learning & Memory, 6, 174-215. SNODGRASS, J. G., & YUDlTSKY, T. (1996). Naming times for the Snodgrass and Vanderwart pictures. Behavior Research Methods, Instruments, & Computers, 28, 516-536. VITKOVITCH, M., & TYRRELL, L. (1995). Sources of disagreement in objcct naming. Quarterly Journal 0/ Experimental Psychology, 48A, 822-848.
English Translation
accordion airplane anchor apple arrow ashtray axe balloon banana basket bear bed bell book boot bottle bow box broom brush bus butterfly button candle cap car carrot cat chain chair cherry chicken church cigar clock clown
Spanish Name
Acordeon Avion Ancla Manzana Flecha Cenicero Hacha Globo Platane Cesta Oso Cama Campana Libro Bota Botella Lazo Caja Escoba Cepillo Autobus Mariposa Beton Vela Gorra Coche Zanahoria Gato Cadena Silla Cereza Gallina Iglesia Puro Reloj (mesa) Payaso 1,015 779 1,062 901 779 896 974 813 724 766 806 735 822 701 756 716 804 907 847 875 803 751 822 757 856 671 775 811 986 685 905 859 982 963 766 789
NamingRT 7.02 .00 2.94 1.75 1.59 1.64 14.00 1.59 .00 .00 .00 .00 1.61 .00 4.92 .00 1.67 6.82 3.33 53.66 3.23 .00 1.61 .00 21.57 .00 .00 .00 1.72 1.67 4.92 3.85 3.33 30.61 .00 .00
% Errors 8 5 5 7 5 8 3 5 7 5 3 4 7 5 4 6 4 4 6 6 7 8 5 4 4 4 8 4 6 4 6 6 7 4 5 6
Phon 4 2 2 3 2 4 2 2 3 2 2 2 3 2 2 3 2 2 3 3 3 4 2 2 2 2 4 2 3 2 3 3 3 2 2 3
Syl 90 100 97 98 92 98 98 100 100 97 98 98 98 100 95 100 98 100 97 89 89 100 98 100 90 95 98 100 95 100 90 95 100 98 95 98
%NA 3.65 3.96 4.18 4.40 1.74 3.00 4.11 4.54 4.36 2.77 3.63 3.49 3.89 3.95 3.29 3.93 3.89 3.37 3.82 3.21 3.62 4.07 4.48 4.08 3.04 2.87 4.53 3.65 4.18 4.47 4.33 4.00 2.62 3.22 4.11 3.11
Imag Agree 1.62 2.44 1.80 4.24 3.03 3.38 1.84 2.57 4.16 2.10 1.81 4.86 2.14 4.82 3.88 4.16 2.22 3.65 3.67 3.90 4.24 2.59 4.13 2.74 2.28 4.44 3.55 3.67 2.04 4.70 3.16 2.46 2.83 2.04 4.60 1.86
Farn 4.25 3.15 2.07 1.54 1.08 2.03 1.68 1.14 1.34 3.71 3.53 2.69 2.31 1.98 2.22 1.29 2.39 1.19 2.29 2.51 4.07 3.53 1.46 1.53 1.76 3.85 2.36 2.71 2.31 2.25 1.31 3.41 3.68 2.85 1.63 4.22
Comp 4 41 7 12 8 10 7 14 3 7 23 206 17 286 5 58 11 60 5 8 27 8 25 27 13 151 5 70 II 66 5 19 109 66 71 6
fAC 23 499 9 201 21 136 27 31 96 42 115 516 66 1784 312 173 99 221 50 75 304 56 181 68 162 1086 37 825 86 1658 52 239 203 24 846 54
ICE 16 221 30 193 52 115 50 83 163 82 160 225 87 264 194 156 124 185 65 102 187 123 147 98 95 259 84 238 106 243 98 190 127 43 231 101
MEC sp 6 88 6 83 10 25 21 39 72 22 41 64 28 109 77 45 27 58 35 37 65 45 51 46 41 160 51 85 55 110 55 59 41 15 118 22
MEC su
22 309 36 276 62 140 71 122 235 104 201 289 115 373 271 201 151 243 100 139 252 168 198 144 136 419 135 323 161 353 153 249 168 58 349 123
MEC to
6.31 4.37 5.61 2.94 4.90 4.86 4.81 3.04 3.33 4.49 4.10 2.49 4.31 3.62 4.26 3.67 4.82 4.10 4.00 4.06 4.35 4.42 4.39 3.90 4.79 3.51 4.30 3.33 5.06 3.37 4.06 3.43 4.62 5.70 4.48 3.44
AoA
The following information is shown for each stimulus: the most common Spanish name from the Snodgrass and Vanderwart (1980) pictures; an English translation; the mean naming RT; the percentage of wrong answers; the word length in number of phonemes (Phon); the word length in number of syllabies (Syl); the percentage ofname agreement (%NA); the means for ratings ofimage agreement (Imag Agree), familiarity (Farn), and complexity (Cornp); adult word frequency (fAC); the frequency for children from the Institute ofEducation (ICE); the Ministry ofEducation spontaneous (MECsp), suggested (MECsu), and total (MECto) measures; and the age-of-acquisition rating (AoA).
APPENDIX
n
Vl Vl
0"-
:r:
(j)
Z
~
[/J
Z
0
Z
~
-
>
rn Z
c ;:d
o-l
'"tl
Spanish Name Peine Vaca Corona Taza Perro Puerta Vestido Tambor Pato Oreja Elefante Sobre Ojo Pez Bandera Flor Tenedor Zorro Rana Satten Jirafa Vaso Gafas Guante Guitarra Martillo Mano Percha Sombrero Corazon Helicoptero Caballo Casa Plancha Canguro Llave Cometa Cuchillo Escalera Lampara Hoja Limon Bombilla
English Translation comb cow crown cup dog door dress drum duck ear elephant envelope eye fish flag flower fork fox frog frying pan giraffe glass glas ses glove guitar hammer hand hanger hat heart helicopter horse house iron kangaroo key kite knife ladder lamp leaf lemon light bulb
NamingRT 714 883 985 768 715 694 765 874 783 679 768 727 642 696 926 691 814 895 805 900 821 676 724 837 763 991 691 775 723 688 871 810 765 806 998 750 812 915 833 835 769 812 745
% Errors 4.92 1.67 1.64 5.08 .00 7.02 4.92 .00 5.00 6.78 .00 25.49 .00 .00 .00 .00 1.61 21.15 11.32 8.77 .00 .00 .00 14.55 .00 .00 .00 1.61 6.67 .00 .00 .00 .00 1.59 1.64 .00 1.64 3.45 .00 .00 1.61 .00 1.64 Phon 5 4 6 4 4 6 7 6 4 5 8 5 3 3 7 4 7 4 4 6 6 4 5 6 7 7 4 5 8 7 10 6 4 6 7 4 6 6 8 7 3 5 7 Syl 2 2 3 2 2 2 3 2 2 3 4 2 2 1 3 1 3 2 2 2 3 2 2 2 3 3 2 2 3 3 5 3 2 2 3 2 3 3 4 3 2 2 3
%NA 100 100 100 94 100 92 92 97 98 94 100 92 100 92 90 100 100 97 86 94 100 100 100 92 100 97 100 100 95 100 98 100 87 100 97 100 100 94 95 100 94 100 100
lmag Agree 4.29 4.15 3.31 3.24 3.40 3.40 2.52 3.78 3.98 4.42 4.16 3.93 4.05 3.62 3.56 3.08 3.64 4.15 4.15 3.55 4.45 3.92 3.62 3.62 4.67 3.04 4.16 3.89 4.05 4.28 3.95 4.16 2.84 3.09 4.40 2.96 4.40 3.04 2.84 2.27 3.60 4.58 4.65
APPENDIX (Continued) Farn 4.49 2.89 1.44 4.68 4.09 4.72 3.77 1.82 2.39 4.49 1.61 3.96 4.74 3.77 2.07 3.90 4.75 1.86 1.99 4.02 1.78 4.83 3.83 3.76 2.92 2.31 4.75 4.18 2.39 3.67 1.82 2.72 4.48 3.52 1.53 4.72 1.83 4.60 2.71 4.20 3.54 3.86 4.15 Comp 2.14 2.97 4.34 2.42 2.88 2.05 2.14 2.22 3.17 2.71 4.15 2.19 3.00 3.34 1.42 2.71 3.37 3.49 2.15 3.12 4.42 1.95 2.20 2.44 2.78 2.36 2.78 1.17 1.20 1.05 3.81 3.63 3.36 3.15 3.86 2.19 2.44 1.49 2.08 1.69 2.42 1.37 2.31
fAC 10 12 21 23 112 410 85 11 5 35 9 2053 96 30 32 59 6 6 5 4 1 60 38 12 19 8 550 7 44 190 2 94 888 6 1 44 18 24 65 27 36 6 8
lCE 124 525 16 69 1101 715 331 38 165 224 225 40 529 223 73 661 219 49 51 47 102 246 712 74 155 72 642 237 108 169 47 545 1321 21 26 148 4 219 134 356 648 78 298
MEC sp 119 202 43 105 250 242 180 66 182 181 205 88 215 221 138 0 197 127 131 97 149 220 266 112 99 119 217 156 103 135 90 240 249 36 47 162 49 188 147 200 242 140 163
MEC su 39 78 15 24 100 91 71 15 48 56 42 23 66 81 36 1 48 28 38 35 24 65 83 62 30 53 67 35 31 28 39 91 137 24 13 44 28 57 56 68 136 59 70
MEC to 158 280 58 129 350 333 251 81 230 237 247 111 281 302 174 I 245 155 169 132 173 285 349 174 129 172 284 191 134 163 129 331 386 60 60 206 77 245 203 268 378 199 233 AoA 3.78 3.68 4.88 3.23 3.00 3.50 4.27 4.60 3.44 3.29 3.55 5.16 3.02 3.67 4.85 3.18 3.14 4.66 3.91 4.81 4.40 2.98 3.98 4.38 4.85 4.65 3.17 4.88 4.15 4.27 5.00 3.64 3.26 4.84 4.92 4.53 4.62 3.12 4.24 4.00 4.12 4.09 4.58
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Spanish Name Le6n Mono Luna Moto Seta Collar Nariz Cebolla Pincel Pantalon Pera Lapiz Pingüino Cerdo Pifia Pipa Jarra Boiso Calabaza Conejo Rinoceronte Anillo Patin Regla Salero Tijeras Foca Oveja Camisa Zapato Falda Caracol Calcetin Araüa Cuchara Ardilla Estrella Fresa Maleta Sol Cisne Jersey Mesa
English Translation lion monkey moon motorcycle mushroom necklace nose onion paintbrush pants pear pencil penguin pig pineapple pipe pitcher pocketbook pumpkin rabbit rhinoceros ring roller skate ruler saltshaker scissors seal sheep shirt shoe skirt snail sock spider spoon squirrel star strawberry suitcase sun swan sweater table
Naming RT 830 845 746 857 775 834 826 976 990 717 731 842 799 949 760 743 952 836 1,308 781 947 1,060 917 803 967 744 931 1,077 990 693 835 790 795 950 723 966 721 751 857 648 952 913 729 % Errors 3.23 .00 .00 1.61 1.69 1.59 .00 1.67 17.65 .00 .00 1.67 .00 1.61 1.69 .00 20.00 6.67 20.41 .00 3.39 1.69 1.72 3.39 19.23 .00 5.08 10.91 12.50 .00 6.78 .00 .00 3.64 .00 1.69 .00 1.64 7.27 .00 28.57 .00 .00 Phon 4 4 4 4 4 5 5 6 6 8 4 5 8 5 4 4 4 5 8 6 11 5 5 5 6 7 4 5 6 6 5 7 8 5 6 6 7 5 6 3 5 6 4
Syl I 2 2 2 2 2 2 3 2 3 2 2 3 2 2 2 2 2 4 3 5 3 2 2 3 3 2 3 3 3 2 3 3 3 3 3 3 2 3 I 2 2 2
%NA 100 90 100 89 95 90 100 95 97 84 100 84 100 92 100 98 89 95 87 100 94 90 92 97 95 94 89 96 97 100 97 98 100 94 90 98 100 100 97 98 90 97 98
Imag Agree 3.95 3.21 4.11 3.20 3.87 4.41 4.09 4.24 3.25 3.33 4.67 4.20 4.42 4.04 4.35 4.30 3.73 2.93 4.24 4.13 3.95 3.27 3.75 4.02 3.42 4.06 3.50 3.56 3.74 3.20 2.91 4.27 3.98 3.24 4.18 4.42 4.40 3.93 3.21 3.22 4.34 3.66 4.27
APPENDIX (Continued) Farn 1.62 1.91 4.12 2.48 2.51 3.26 4.59 3.68 2.38 4.84 3.66 4.65 1.53 2.38 2.89 1.60 3.88 3.88 1.94 2.31 1.52 3.98 2.24 3.51 3.31 4.14 1.55 2.19 4.40 4.46 3.81 2.57 4.69 2.52 4.72 2.14 3.49 3.51 3.28 4.46 2.30 4.75 4.69 Comp 3.80 3.71 1.14 4.56 3.71 1.59 1.73 2.36 1.81 1.98 1.19 1.68 2.58 3.17 3.95 1.71 1.81 2.61 2.12 3.31 3.00 1.64 3.95 2.61 2.51 4.53 2.86 3.46 2.85 3.17 1.36 2.66 1.61 3.19 1.86 3.29 1.19 2.47 3.19 2.32 3.07 2.73 1.41
fAC 28 24 80 10 2 14 71 18 7 31 10 10 3 17 3 19 8 19 3 9 I 20 I 36 I 5 5 5 61 17 37 11 3 9 4 22 48 4 24 289 5 10 235 ICE 417 131 231 266 12 III 324 34 43 953 166 1396 17 155 25 77 44 267 8 179 69 391 37 421 8 108 24 153 531 1115 444 40 511 36 232 20 160 47 271 329 30 688 1973
MEC sp 254 176 184 206 56 133 196 86 90 262 193 250 46 154 87 76 68 133 20 190 104 167 68 205 17 133 80 155 212 250 193 115 240 85 199 91 164 128 108 220 26 213 323 MEC su 56 46 62 91 29 42 35 52 29 109 80 96 22 51 41 33 21 45 18 67 23 49 41 51 2 46 25 54 70 109 67 50 85 23 56 21 63 58 43 102 10 73 121
MEC to 310 222 246 297 85 175 231 138 119 371 273 346 68 205 128 109 89 178 38 257 127 216 109 256 19 179 105 209 282 359 260 165 325 108 255 112 227 186 151 322 36 286 444 AoA 4.08 4.40 3.90 4.12 5.25 4.44 3.32 5.06 4.91 3.85 3.65 3.48 4.65 3.77 4.83 5.72 4.26 4.72 5.45 3.67 5.27 4.78 4.79 4.80 5.08 4.08 5.34 3.88 4.20 3.20 4.10 3.88 3.28 4.59 3.16 4.80 4.04 4.08 4.54 3.08 5.11 3.83 3.55
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Spanish English Name Translation Naming RT Telefono telephone 709 Raqueta tennis racket 858 Dedal thimb1e 861 Corbata tie 782 Tigre tiger 819 Tomate tomato 906 Tren train 899 Arbol tree 734 Camion truck 912 Trompeta trumpet 870 Paraguas umbrella 678 Jarron vase 912 Cha1eco vest 938 Reloj (pulsera) watch 752 Regadera watering can 1,098 Rueda wheel 748 Ventana window 998 Copa wineglass 768 % Errors .00 1.64 5.00 .00 3.28 3.23 .00 .00 7.55 .00 1.59 9.26 3.39 .00 5.08 .00 1.61 12.28
Syl 4 3 2 3 2 3 1 2 2 3 3 2 3 2 4 2 3 2 98 98
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%NA 100 100 95 100 90 98 95 97 98 94 98 94 95 86 98 4.04 2.69 3.80 2.33 4.13 3.84 2.15 3.72
lmag Agree 4.11 4.27 4.34 4.19 3.06 3.82 3.42 3.89 3.15 Farn 4.87 2.30 2.48 2.11 1.60 3.74 3.35 3.98 3.02 1.78 4.16 3.02 2.37 4.77 1.95 2.39 4.55 4.05
(Manuseript reeeivedOctober27, 1998; revision aeeeptedfor publieation April 27, 1999.)
Phon 8 6 5 7 5 6 4 5 6 8 8 5 6 5 8 5 7 4
APPENDIX (Continued) Comp 1.59 3.19 2.22 2.32 2.46 3.58 3.05 3.95 2.59 4.19 2.85 2.93 2.46 2.12 3.31 1.46 2.92 1.71 fAC 93 2 1 26 7 6 55 55 13 5 18 5 18 71 0 25 163 62
ICE 121 44 29 150 258 72 328 968 509 30 285 129 26 846 10 106 915 42
MEC sp 158 100 37 89 209 149 169 267 225 59 123 131 98 231 24 162 249 95
MEC su 81 30 12 25 36 65 71 139 106 14 57 30 31 118 14 58 95 44
MEC to 239 130 49 114 245 214 240 406 331 73 180 161 129 349 38 220 344 139 AoA 4.27 5.10 5.10 5.10 4.85 3.90 4.37 3.65 3.86 5.15 4.18 4.65 5.78 4.28 4.52 3.82 3.88 3.82
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