Semantic Richness Effects in Spoken Word Recognition: A Lexical Decision and Semantic Categorization Megastudy

Abstract

A large number of studies have demonstrated that semantic richness dimensions [e.g., number of features, semantic neighborhood density, semantic diversity , concreteness, emotional valence] influence word recognition processes. Some of these richness effects appear to be task-general, while others have been found to vary across tasks. Importantly, almost all of these findings have been found in the visual word recognition literature. To address this gap, we examined the extent to which these semantic richness effects are also found in spoken word recognition, using a megastudy approach that allows for an examination of the relative contribution of the various semantic properties to performance in two tasks: lexical decision, and semantic categorization. The results show that concreteness, valence, and number of features accounted for unique variance in latencies across both tasks in a similar direction—faster responses for spoken words that were concrete, emotionally valenced, and with a high number of features—while arousal, semantic neighborhood density, and semantic diversity did not influence latencies. Implications for spoken word recognition processes are discussed.

MEGALEX: A megastudy of visual and auditory word recognition

“…Concerning the auditory modality, stimulus duration is the most important variable (accounting for 46% of the variance in our study), which is consistent with the results of a previous relatively large-scale study conducted in Table 11 Percentages of variance explained for the visual lexical decision task (14,868 words in common with the auditory lexical decision task) and for frequency, word length (in letters) and orthographic similarity ( Dutch (Ernestus & Cutler, 2015; see also Goh et al, 2016). The extra contribution of frequency is around 4% and the extra contribution of number of phonemes is 1.5%.…”

“…However, we showed that words that are phonologically similar to many other words (i.e., with low PLD20 values) were responded to faster than phonologically dissimilar words (i.e., with high PLD20 values). This latter result departs from the general finding that, in the auditory modality, words with more similar sounding (or closer phonological neighbors) are usually recognized more slowly than more distinct word-forms (e.g., Goh et al, 2009;Goh et al, 2016;Suárez, Tan, Yap, & Goh, 2011;Ziegler et al, 2003), but it converges with the general finding that, in the visual modality, words that are orthographically similar to many other words are responded to faster than orthographically dissimilar words (e.g., Brysbaert et al, 2016;Ferrand et al, 2010;Keuleers, Diependaele, & Brysbaert, 2010;Keuleers et al, 2012). Concerning phonological uniqueness point, our results are consistent with the general finding that words with an early phonological uniqueness point are responded to faster than words with a late phonological uniqueness point (e.g., Radeau & Morais, 1990;Radeau et al, 2000;Radeau et al, 1989).…”

“…More recently, Goh, Yap, Lau, Ng, and Tan (2016) collected auditory lexical decision (and semantic categorization) data for 514 nouns from 80 participants. The goal of their study was to determine the unique contribution of semantic richness variables (such as concreteness, number of semantic features, and emotional valence), above and beyond the contribution of lexical variables (such as word duration, frequency, structural properties, and number of morphemes) to auditory word recognition.…”

Age-Dependent Positivity-Bias in Children’s Processing of Emotion Terms

“…Studies using the VDT with positive and negative affective words (e.g., Võ et al, 2006; Goh et al, 2016) and emotion terms (Feyereisen et al, 1986) report faster reactions when participants were asked to categorize positive word stimuli compared to negative ones. LDTs also found evidence for enhanced word processing in positive words: Participants were faster at identifying positive compared to negative words (Kuchinke et al, 2005, 2007; Kanske and Kotz, 2007; Hofmann et al, 2009; Scott et al, 2009, 2014; Palazova et al, 2011; Bayer and Schacht, 2014; Ferré and Sanchez-Casas, 2014; Kuperman et al, 2014; Ponari et al, 2015; Yao et al, 2016).…”

Context-based facilitation in visual word recognition: Evidence for visual and lexical but not pre-lexical contributions

“…However, given that investigations of knowledge and context effects on word recognition have so far been strongly confounded with semantics, it is at present still an open question whether knowledge-and context-based facilitation can be realized without semantic information -i.e., based on orthographic information alone. For example, word frequency, which is often used as a proxy for word knowledge (e.g., Coltheart et al, 2001), is not only associated with orthographic properties (e.g., correlations with orthographic neighborhood around .5; Yap et al, 2012) but also with semantic characteristics of words (e.g., correlations with semantic neighborhood around .75; Goh et al, 2016;Yap et al, 2012). Even more so, contextual effects on word processing typically depend upon semantic information from, e.g., the preceding sentence (e.g., "…”