German normative data with naming latencies for 283 action pictures and 600 action verbs
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Timed picture naming is a common psycholinguistic paradigm. In this task, participants are asked to label visually depicted objects or actions. Naming performance can be influenced by several picture and verb characteristics which demands fully characterized normative data. In this study, we provide a first German normative data set of picture and verb characteristics associated with a compilation of 283 freely available action pictures and 600 action verbs including naming latencies from 55 participants. We report standard measures for pictures and verbs such as name agreement indices, visual complexity, word frequency, word length, imageability and age of acquisition. In addition, we include less common parameters, such as orthographic Levenshtein distance, transitivity, reflexivity, morphological complexity, and motor content of the pictures and their associated verbs. We use repeated measures correlations in order to investigate associations between picture and word characteristics and linear mixed effects modeling for the prediction of naming latency. Our analyses reveal comparable results to previous studies in other languages, indicating high construct validity. We found that naming latency varied as a function of entropy of responses, word frequency and motor content of pictures and words. In summary, we provide first German normative data for action pictures and their associated verbs and identify variables influencing naming latency.Keywords:
Levenshtein distance
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The aim of this study was to address the effect of objective age of acquisition (AoA) on picture-naming latencies when different measures of frequency (cumulative and adult word frequency) and frequency trajectory are taken into account. A total of 80 Spanish participants named a set of 178 pictures. Several multiple regression analyses assessed the influence of AoA, word frequency, frequency trajectory, object familiarity, name agreement, image agreement, image variability, name length, and orthographic neighbourhood density on naming times. The results revealed that AoA is the main predictor of picture-naming times. Cumulative frequency and adult word frequency (written or spoken) appeared as important factors in picture naming, but frequency trajectory and object familiarity did not. Other significant variables were image agreement, image variability, and neighbourhood density. These results (a) provide additional evidence of the predictive power of AoA in naming times independent of word-frequency and (b) suggest that image variability and neighbourhood density should also be taken into account in models of lexical production.
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Neighbourhood (mathematics)
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Megastudies with processing efficiency measures for thousands of words allow researchers to assess the quality of the word features they are using. In this article, we analyse reading aloud and lexical decision reaction times and accuracy rates for 2,336 words to assess the influence of subjective frequency and age of acquisition on performance. Specifically, we compare newly presented word frequency measures with the existing frequency norms of Kucera and Francis (1967), HAL (Burgess & Livesay, 1998), Brysbaert and New (2009), and Zeno, Ivens, Millard, and Duvvuri (1995). We show that the use of the Kucera and Francis word frequency measure accounts for much less variance than the other word frequencies, which leaves more variance to be "explained" by familiarity ratings and age-of-acquisition ratings. We argue that subjective frequency ratings are no longer needed if researchers have good objective word frequency counts. The effect of age of acquisition remains significant and has an effect size that is of practical relevance, although it is substantially smaller than that of the first phoneme in naming and the objective word frequency in lexical decision. Thus, our results suggest that models of word processing need to utilize these recently developed frequency estimates during training or setting baseline activation levels in the lexicon.
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Phonological similarity among spoken words is traditionally indexed by neighbourhood density (i.e., the number of words differing by a single phoneme from the target). However, density is of limited utility for long words, which have few or no neighbours. In this study, we explored the effects of phonological similarity and word-frequency on auditory lexical decision performance, using multisyllabic words with no neighbours and a new similarity metric called phonological Levenshtein distance (PLD20), which reflects the mean number of substitution, insertion, or deletion operations required to transform a word into 20 of its closest Levenshtein neighbours. Inhibitory effects of PLD20 were observed, where words with closer neighbours were recognised slower; importantly, these effects were present for only low-frequency words, replicating previous findings with other neighbourhood measures. The properties of PLD20 make it a promising new measure for quantifying the phonological distinctiveness of multisyllabic words in spoken word recognition research.
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Optimal distinctiveness theory
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Abstract A review of multitask investigations on the locus of the age-of-acquisition (AoA) effect in the English, Dutch, and French languages reveals two main findings. First, for most tasks there is near perfect correlation between the magnitude of the AoA effect and the magnitude of the frequency effect, even though the stimuli were selected so that both variables were orthogonal. This frequency-related AoA effect is as large as the frequency effect, despite the fact that the range of AoA values is more restricted than the range of frequency values. Second, a frequency-independent AoA effect is observed in object naming and word associate generation. Different explanations of the frequency-related and the frequency-independent AoA effects are reviewed and evaluated. Notes 1β-values or standardized regression coefficients are obtained when the regression analysis is done on the z-values of the dependent and the independent variables. In this way, the values are not influenced by differences in the variance of the independent variables (see Aron & Aron, Citation2003, pp. 114–124, for a good explanation). 2Notice that this exactly may be what the tachistoscopic presentation of Moore et al. induced: A need to covertly name the briefly presented stimulus, so that it could be kept in short-term memory. 3Interestingly, Levelt and colleagues never refer to their stimuli as polysemous words. They always refer to them as homophones and give examples of English heterographic homophones when they describe their manipulation (e.g., they say the words were of the type wee–we, moor–more, whereas in reality their stimuli were of the type bank, which can be translated in two different ways in Dutch, depending on whether it refers to a river or to money).
Age of Acquisition
Homophone
Stimulus (psychology)
Variables
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Concreteness
Age of Acquisition
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Concreteness
Age of Acquisition
Bigram
Orthography
Pronunciation
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Age of Acquisition
Word length
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Three hypotheses for effects of age of acquisition (AoA) in lexical processing are compared: the cumulative frequency hypothesis (frequency and AoA both influence the number of encounters with a word, which influences processing speed), the semantic hypothesis (early-acquired words are processed faster because they are more central in the semantic network), and the neural network model (early-acquired words are faster because they are acquired when a network has maximum plasticity). In a regression study of lexical decision (LD) and semantic categorization (SC) in Italian and Dutch, contrary to the cumulative frequency hypothesis, AoA coefficients were larger than frequency coefficients, and, contrary to the semantic hypothesis, the effect of AoA was not larger in SC than in LD. The neural network model was supported. Effects of word frequency (high-frequency words are processed faster than low-frequency words) and age of acquisition (AoA; early-acquired words are processed faster than late-acquired words) in lexical processing are by now widely accepted as they are found in many different studies and many different tasks (see Ghyselinck, Lewis, & Brysbaert, 2004, for a review). Although these effects are both very stable, the question of where they originate has not been settled. In particular, the effect of word AoA has been less accommodated in models of lexical processing than has the effect of word frequency.
Age of Acquisition
Semantic network
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Word list
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