Consistency norms for 37,677 english words

Revisiting the concreteness effect: Non-arbitrary mappings between form and concreteness of English words influence lexical processing

How do we represent and process abstract and concrete concepts? The "concreteness effect", in which words with more concrete meanings are processed more quickly and accurately across a range of language tasks compared to abstract ones, suggests a differential conceptual organization of these words in the brain. However, concrete words tend to be marked by specific phonotactic features, such as having fewer syllables and more phonological neighbours. It is unclear whether these non-arbitrary form-meaning relationships that systematically denote the concreteness of a word impact language processing. In the current study, we first establish the extent of systematic mappings between phonological/phonetic features and concreteness ratings in a large set of monosyllabic and polysyllabic English words (i.e., concreteness form typicality), then demonstrate that they significantly influence lexical processing using behavioural megastudy datasets. Surface form features predicted a significant proportion of variance in concreteness ratings of monomorphemic words (25 %) which increased with the addition of polymorphemic forms (43 %). In addition, concreteness form typicality was a significant predictor of performance on visual and auditory lexical decision, naming, and semantic (concrete/abstract) decision tasks, after controlling for a range of psycholinguistic variables and concreteness ratings. Overall, our results provide the first evidence that concreteness form typicality influences lexical processing. We discuss theoretical implications for interpretations of the concreteness effect and models of language processing that have yet to incorporate non-arbitrary relationships between form and meaning into their feature sets.

The English Sublexical Toolkit: Methods for indexing sound-spelling consistency

This work introduces the English Sublexical Toolkit, a suite of tools that utilizes an experience-dependent learning framework of sublexical knowledge to extract regularities from the English lexicon. The Toolkit quantifies the empirical regularity of sublexical units in both the reading and spelling directions (i.e., grapheme-to-phoneme and phoneme-to-grapheme) and at multiple grain sizes (i.e., phoneme/grapheme and onset/rime unit size). It can extract multiple experience-dependent regularity indices for words or pseudowords, including both frequency indices (e.g., grapheme frequency) and conditional probability indices (e.g., grapheme-to-phoneme probability). These tools provide (1) superior estimates of the regularities that better reflect the complexity of the sublexical system relative to previously published indices and (2) completely novel indices of sublexical units such as phonographeme frequency (i.e., combined units of individual phonemes and graphemes that are independent of processing direction). We demonstrate that measures from the toolkit explain significant amounts of variance in empirical data (naming of real words and lexical decision), and either outperform or are comparable to the best available consistency measures. The flexibility of the toolkit is further demonstrated by its ability to readily index the probability of different pseudowords pronunciations, and we report that the measures account for the majority of variance in these empirically observed probabilities. Overall, this work provides a framework and resources that can be flexibly used to identify optimal corpus-based consistency measures that help explain reading/spelling behaviors for real and pseudowords.

HeLP: The Hebrew Lexicon project

Lexicon projects (LPs) are large-scale data resources in different languages that present behavioral results from visual word recognition tasks. Analyses using LP data in multiple languages provide evidence regarding cross-linguistic differences as well as similarities in visual word recognition. Here we present the first LP in a Semitic language-the Hebrew Lexicon Project (HeLP). HeLP assembled lexical decision (LD) responses to 10,000 Hebrew words and nonwords, and naming responses to a subset of 5000 Hebrew words. We used the large-scale HeLP data to estimate the impact of general predictors (lexicality, frequency, word length, orthographic neighborhood density), and Hebrew-specific predictors (Semitic structure, presence of clitics, phonological entropy) of visual word recognition performance. Our results revealed the typical effects of lexicality and frequency obtained in many languages, but more complex impact of word length and neighborhood density. Considering Hebrew-specific characteristics, HeLP data revealed better recognition of words with a Semitic structure than words that do not conform to it, and a drop in performance for words comprising clitics. These effects varied, however, across LD and naming tasks. Lastly, a significant inhibitory effect of phonological ambiguity was found in both naming and LD. The implications of these findings for understanding reading in a Semitic language are discussed.

Non-arbitrary mappings between size and sound of English words: Form typicality effects during lexical access and memory

A century of research has provided evidence of limited size sound symbolism in English, that is, certain vowels are non-arbitrarily associated with words denoting small versus large referents (e.g., /i/ as in teensy and /ɑ/ as in tall). In the present study, we investigated more extensive statistical regularities between surface form properties of English words and ratings of their semantic size, that is, form typicality, and its impact on language and memory processing. Our findings provide the first evidence of significant word form typicality for semantic size. In five empirical studies using behavioural megastudy data sets of performance on written and auditory lexical decision, reading aloud, semantic decision, and recognition memory tasks, we show that form typicality for size is a stronger and more consistent predictor of lexical access during word comprehension and production than semantic size, in addition to playing a significant role in verbal memory. The empirical results demonstrate that statistical information about non-arbitrary form-size mappings is accessed automatically during language and verbal memory processing, unlike semantic size that is largely dependent on task contexts that explicitly require participants to access size knowledge. We discuss how a priori knowledge about non-arbitrary form-meaning associations in the lexicon might be incorporated in models of language processing that implement Bayesian statistical inference.

Spelling-to-pronunciation transparency ratings for the 20,000 most frequently written English words

Given English orthography's quasi-regular nature, applying common decoding rules to a word does not always result in a correct pronunciation matching the stored phonological form (e.g., the word tongue). To arrive at a correct pronunciation, developing readers must make the match between a decoded pronunciation and a word's correct pronunciation stored in memory. Developmentally, this matching process varies as a function of child skill (e.g., decoding, vocabulary) and word characteristics (e.g., spelling-to-pronunciation transparency, concreteness), with each being continuously distributed. Spelling-to-pronunciation transparency ratings represent a global measure of the ease of arriving at a word's correct pronunciation from its decoded pronunciation and in experimental studies has been shown to be a critical dimension in assessing the difficulty of a word for developing readers (e.g., Steacy et al., 2022a, 2022b). This study aimed to create a database of spelling-to-pronunciation transparency ratings for the 23,282 most frequently written English words, made available in the supplemental materials for future analyses. We asked adults to rate words' spelling-to-pronunciation transparency on a scale of 1-6 (1 = very easy to match, 6 = very difficult). Results of multiple regression analyses revealed variance in ratings to be unaccounted for by other word features, demonstrating the uniqueness of these ratings. Furthermore, words that are considered irregular, classified previously as strange, or contained at least one schwa received higher ratings, demonstrating strong associations between transparency and regularity. Lastly, these ratings significantly predicted both adult word naming time and child word reading accuracy above and beyond other word features known to predict reading.

Spelling monosyllabic English words

We conducted a megastudy to examine the spelling of American English monosyllables with typewritten responses. We related both sublexical and lexical/semantic factors to spelling accuracy and reaction time (RT) for the first keypress and response duration for spelling 1,856 monophonic monosyllables. We found that (a) each of 13 predictor variables was significantly related to performance for at least one measure, (b) orthographic length was unrelated to the first key RT, but did relate to accuracy and response duration, (c) sound-spelling and spelling-sound consistency was related to performance, and in particular, onset consistency related to accuracy and first key RT, but was unrelated to response duration, (d) contextual diversity was consistently related to performance across all measures, and (e) age of acquisition (AoA) was related to all measures, but was related more to the first key RT than response duration. The results indicate that people begin the spelling process once they identify the first letter, and they continue to process the spelling pattern as the response unfolds. These results are best explained by a parallel-distributed-processing framework.

Orthography-phonology consistency in English: Theory- and data-driven measures and their impact on auditory vs. visual word recognition

Research on orthographic consistency in English words has selectively identified different sub-syllabic units in isolation (grapheme, onset, vowel, coda, rime), yet there is no comprehensive assessment of how these measures affect word identification when taken together. To study which aspects of consistency are more psychologically relevant, we investigated their independent and composite effects on human reading behavior using large-scale databases. Study 1 found effects on adults' naming responses of both feedforward consistency (orthography to phonology) and feedback consistency (phonology to orthography). Study 2 found feedback but no feedforward consistency effects on visual and auditory lexical decision tasks, with the best predictor being a composite measure of consistency across grapheme, rime, OVC, and word-initial letter-phoneme. In Study 3, we explicitly modeled the reading process with forward and backward flow in a bidirectionally connected neural network. The model captured latent dimensions of quasi-regular mapping that explain additional variance in human reading and spelling behavior, compared to the established measures. Together, the results suggest interactive activation between phonological and orthographic word representations. They also validate the role of computational analyses of language to better understand how print maps to sound, and what properties of natural language affect reading complexity.

SCOPE: The South Carolina psycholinguistic metabase

The number of databases that provide various measurements of lexical properties for psycholinguistic research has increased rapidly in recent years. The proliferation of lexical variables, and the multitude of associated databases, makes the choice, comparison, and standardization of these variables in psycholinguistic research increasingly difficult. Here, we introduce The South Carolina Psycholinguistic Metabase (SCOPE), which is a metabase (or a meta-database) containing an extensive, curated collection of psycholinguistic variable values from major databases. The metabase currently contains 245 lexical variables, organized into seven major categories: General (e.g., frequency), Orthographic (e.g., bigram frequency), Phonological (e.g., phonological uniqueness point), Orth-Phon (e.g., consistency), Semantic (e.g., concreteness), Morphological (e.g., number of morphemes), and Response variables (e.g., lexical decision latency). We hope that SCOPE will become a valuable resource for researchers in psycholinguistics and affiliated disciplines such as cognitive neuroscience of language, computational linguistics, and communication disorders. The availability and ease of use of the metabase with comprehensive set of variables can facilitate the understanding of the unique contribution of each of the variables to word processing, and that of interactions between variables, as well as new insights and development of improved models and theories of word processing. It can also help standardize practice in psycholinguistics. We demonstrate use of the metabase by measuring relationships between variables in multiple ways and testing their individual contribution towards a number of dependent measures, in the most comprehensive analysis of this kind to date. The metabase is freely available at go.sc.edu/scope.

Distinct neural sources underlying visual word form processing as revealed by steady state visual evoked potentials (SSVEP)

EEG has been central to investigations of the time course of various neural functions underpinning visual word recognition. Recently the steady-state visual evoked potential (SSVEP) paradigm has been increasingly adopted for word recognition studies due to its high signal-to-noise ratio. Such studies, however, have been typically framed around a single source in the left ventral occipitotemporal cortex (vOT). Here, we combine SSVEP recorded from 16 adult native English speakers with a data-driven spatial filtering approach—Reliable Components Analysis (RCA)—to elucidate distinct functional sources with overlapping yet separable time courses and topographies that emerge when contrasting words with pseudofont visual controls. The first component topography was maximal over left vOT regions with a shorter latency (approximately 180 ms). A second component was maximal over more dorsal parietal regions with a longer latency (approximately 260 ms). Both components consistently emerged across a range of parameter manipulations including changes in the spatial overlap between successive stimuli, and changes in both base and deviation frequency. We then contrasted word-in-nonword and word-in-pseudoword to test the hierarchical processing mechanisms underlying visual word recognition. Results suggest that these hierarchical contrasts fail to evoke a unitary component that might be reasonably associated with lexical access.