Does frequency trajectory influence word identification? A cross-task comparison

Abstract

In a series of six experiments, the influence of frequency trajectory in visual word recognition was investigated. In Experiment 1, frequency trajectory was found to exert a strong and reliable influence on age of acquisition (AoA) ratings. In word reading (Experiment 2), lexical decision (Experiments 3 and 6), proper name decision (Experiment 4), progressive demasking (Experiment 5), and a multiple regression analysis of lexical decision times taken from the French Lexicon Project, the effect of frequency trajectory was not reliable. In contrast, in all the experiments and in the multiple regression analysis, cumulative frequency had a strong and reliable influence on word recognition times. The findings firmly establish that in alphabetic languages such as French, age-limited learning effects do not surface readily in word recognition. In contrast, the total exposure to words across the lifetime is a strong determinant of word recognition speed. The implications of the findings are discussed.

Keywords:

• Word recognition
• Frequency trajectory
• Cumulative frequency
• Lexical decision
• Word reading
• Progressive demasking

Acknowledgments

The authors wish to thank very much Marc Brysbaert, Padraic Monaghan, Miguel Pérez, and an anonymous reviewer for helpful and challenging comments on a previous version of the paper. We are grateful to Sébastien Roux for conducting Experiment 1 and Experiment 2, and to Emma Forin and Clothilde Joly for conducting Experiment 4.

Notes

¹ We accept that both objective (written and spoken) word frequency and frequency trajectory are also influenced by the behaviour of human beings (i.e., some words are more frequent because individuals produce or read them more often than others). In our view, objective or rated AoA scores are characterized as a behavioural outcome because the way they are measured directly depends on the performance of participants (naming accuracy in children, ratings in adults). In contrast, word frequency and frequency trajectory are derived from corpus analyses. They indicate the number of times a word is found in a corpus. This is the reason why we qualify the former measures, but not the latter, as “more objective”.

² Free access to Manulex and Manulex-infra can be obtained online at http://www.manulex.org/

³ Lété, Peereman, and Fayol (2008) showed that GP and PG consistency values, calculated among words used in one and the same grade, were very similar across grades, thus indicating that the complexity of the French orthographic system is already captured in the early reader's vocabulary. Thus, words that are inconsistent for first-grade children remain inconsistent in higher grades, and there is no sharp modification in their levels of GP or PG ambiguity (see also Peereman et al., 2007, for a description of the French writing system at an infralexical level).

⁴ Frequency values taken from Lexique (New, Pallier, Brysbaert, & Ferrand, 2004) instead of the Manulex G3–5 lexicon continued to reflect the critical difference between the two conditions. Level frequencies were 26 per million for LH words and 159 per million for LH words, t(30) = -4.45, p  <  .01, giving a cumulative-frequency value of 228 per million and 186 per million, respectively, t(30) = 1.26, p  >  .10.

⁵ As far as the relationship between frequency trajectory and rated AoA is concerned, it is possible to ask why subsequent changes in frequency over time would affect the AoA of words. We accept that the frequency of exposure during childhood is undoubtedly the most important factor if a word is to be learned. One advantage of using frequency trajectory rather than directly using child frequency to investigate age-limited learning effects lies in the fact that frequency trajectory provides information concerning the way words have been encountered during childhood compared to adulthood for a given level of cumulative frequency. This relative information would be lost if child frequency was used. We thank Miguel Pérez very much for pointing out this interesting issue.

⁶ It could be asked whether the use of different softwares (PsyScope versus DMDX) or different computers or keyboards might influence the precision of the collected reaction time (RT) data and the comparability of different results obtained across experiments. However, as shown by Damian (2010), given the variability of human performance in standard behavioural tasks, such as those used in the current study, the measurement errors related to the imprecision of input devices (e.g., computer keyboards) are bound to be very small.

⁷ Indeed, using the FLP corpus (Ferrand et al., 2010), we ran a regression analysis restricted to very inconsistent words. Frequency trajectory was reliable but acted in the opposite direction to that predicted. There is no straightforward way to account for this reversed frequency trajectory effect, and it may possibly be due to strategic factors involved in lexical decision when participants are confronted with very inconsistent items. However, it should be remembered that while the prediction of age-limited effects on very inconsistent items is undoubtedly critical for word naming, this is not the case for lexical decision because GP effects are stronger in word naming than in lexical decision.