The perceptual structure of printed words: The case of silent E words in French

Journal of Memory and Language 97 (2017) 121–134

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The perceptual structure of printed words: The case of silent E words in French Fabienne Chetail ⇑, Alain Content LCLD, CRCN, Université Libre de Bruxelles (ULB), Belgium

a r t i c l e

i n f o

Article history: Received 19 May 2016 Revision received 11 July 2017 Available online 9 August 2017 Keywords: CV pattern silent E Spoken and written modality Unit counting Word length estimation

a b s t r a c t According to a widespread view on functional units in word reading, the perceptual structure of printed words is constrained by print-to-speech mappings. Here, we examined the hypothesis that the organization of consonant and vowel letters (the CV pattern) determines the perceived structure of letter strings. Skilled readers were presented with two kinds of bisyllabic French words. Half of the words included a silent E between two consonants (e.g., gobelet, /gɔble/) thus entailing three orthographic vowel groups, while the other half were control words with two vowel groups (e.g., crémeux, /kʀemø/). Participants had to decide on the number of units or reproduce the physical length of the stimuli. Silent E words were consistently estimated to be longer (more units, longer lines) than control words, despite being matched in number of letters and phonemes. The effect was present both in the written modality (Experiments 1A–1B) and in the spoken modality (Experiments 2A-2B). When prereaders and beginning readers with limited knowledge of the orthographic form of words performed the tasks (Experiments 3A-3B), no bias was found, confirming its orthographic nature in skilled readers. The study provides a clear confirmation of the predictions based on the CV pattern hypothesis according to which the number of vowel letter clusters determines the perceived units of letter strings. Ó 2017 Elsevier Inc. All rights reserved.

Introduction One basic question in the field of visual word recognition concerns the nature of orthographic representations intervening between letter and word codes. The investigation of the nature of higher-order units involved in polysyllabic letter strings may have been hindered by the focus of much research on monosyllabic words, in spite of the predominance of longer words in the lexicon (e.g., Brand, Rey, & Peereman, 2003; Jared & Seidenberg, 1990; Mousikou, Sadat, Lucas, & Rastle, 2017; Yap & Balota, 2009). Nevertheless, the issue has been of interest since the earliest times of research on reading (Huey, 1908). It was actively examined in the 1980’s (e.g., Prinzmetal, Treiman, & Rho, 1986; Santa, Santa, & Smith, 1977), somewhat left aside later on, and brought back more recently, spurred by the intent to model polysyllabic word reading (e.g., Chetail & Content, 2012; Conrad, Tamm, Carreiras, & Jacobs, 2010; Perry, Ziegler, & Zorzi, 2010). Determining what processing units are involved in the early steps of written word identification and how the perceptual processing system organizes ⇑ Corresponding author at: Laboratoire Cognition Langage, & Développement (LCLD), Centre de Recherche Cognition et Neurosciences (CRCN), Université Libre de Bruxelles (ULB) - Av. F. Roosevelt, 50 / CP 191 - 1050 Brussels, Belgium. E-mail address: [email protected] (F. Chetail). http://dx.doi.org/10.1016/j.jml.2017.07.007 0749-596X/Ó 2017 Elsevier Inc. All rights reserved.

letter strings (i.e., orthographic parsing) thus remains a recurrent question in the field. In the present study, we examine the hypothesis that the organization of consonant and vowel letters determines orthographic parsing. There are several reasons to postulate the existence of intermediate representations corresponding to groups of several letters. First, they may provide an elegant solution for encoding the relative position of letters (e.g., Grainger & Van Heuven, 2003; Whitney, 2001). Second, given that most alphabetic writing systems include multi-letter graphemes (see Van den Bosch, Content, Daelemans, & De Gelder, 1994), letter clusters must be extracted to encode print-to-sound associations. Furthermore, higher-order units such as syllables may be necessary to permit the generalisation of print-sound knowledge across positions (see e.g., Perry et al., 2010). In addition, units coding for multi-letter clusters in the hierarchy of neural detectors involved in orthographic processing may be a consequence of neurophysiological constraints, given that receptive fields at successive levels increase only gradually in size (e.g., Dehaene, Cohen, Sigman, & Vinckier, 2005). A common view is that the structure of word representations is constrained by print-to-speech associations, so that printed units map onto spoken linguistic units (phonemes or syllables, e.g., Coltheart, 1978; Conrad, Grainger, & Jacobs, 2007; Spoehr &

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Smith, 1973). This view has been strengthened by evidence that long words are structured into syllable-sized units (e.g., Alvarez, Carreiras, & Perea, 2004; Carreiras, Alvarez, & De Vega, 1993; Chetail & Mathey, 2009; Conrad & Jacobs, 2004; Conrad et al., 2007; Mathey & Zagar, 2002; Muncer & Knight, 2012). However, the question of the cues sustaining the parsing process in written words has been less investigated, probably due in part to the lack of precision in the use of the term ‘syllable’. From a linguistic viewpoint, the word ‘syllable’ refers to a phonetic or phonological constituent, but in most psycholinguistic studies in the written modality, the term was used to refer both to phonological syllables and to their orthographic counterpart. This may have obscured the need to explain how letter strings are structured into letter clusters and how these map onto spoken syllables. On the contrary, in orthographic approaches to parsing, the issue of the cues sustaining word segmentation took precedence over the definition of units per se. Probably the most representative illustration of this view is the hypothesis that letter cluster frequencies are prominent parsing cues (e.g., Adams, 1981; Seidenberg, 1987). Because there are stronger sequential constraints within syllables than across syllables, bigrams straddling graphosyllable boundaries are generally less frequent than bigrams flanking the boundaries, and this pattern might provide an orthographic clue to segmentation which often coincides with the spoken syllable boundary. However, direct tests did not fully support this hypothesis (e.g., Conrad, Carreiras, Tamm, & Jacobs, 2009; Doignon & Zagar, 2005; Muncer & Knight, 2012; Rapp, 1992). Another orthographic hypothesis is that the perceptual structure of letter strings is determined by the orthographic organization of consonant and vowel letters (i.e., the CV pattern), with each vowel or cluster of adjacent vowel letters underlying a perceptual unit (e.g., Chetail & Content, 2012; Chetail & Content, 2013; Chetail & Content, 2014; Chetail, Drabs, & Content, 2014; see also Buchwald & Rapp, 2006; Caramazza & Miceli, 1990, in spelling production). Chetail and Content (2012) showed for example that in a syllable counting task, in which participants had to determine the number of spoken syllables in French written words, responses were slower for bisyllabic words that had only one orthographic vowel cluster (e.g., chaos, /ka.o/) than for control words (e.g., fatal, /fa.tal/, two vowel clusters and two syllables) in which the number of vowel letter clusters and the number of spoken syllables matched. In words like chaos or client (referred to as hiatus words), there is a mismatch between the number of vowel clusters (client: one) and the number of syllables (/klaɪ.ənt/: two) due to the presence of two or more adjacent vowel letters that map onto two or more adjacent vowel phonemes (hiatus pattern). Error analyses further showed that participants were prone to count the number of vowel clusters rather than the number of syllables, even though they resorted to subvocal articulation to respond (see also Chetail, Scaltritti, & Content, 2014, in Italian; Chetail, Treiman, Content, 2016, in English). Importantly, evidence of an influence of the CV pattern was reported not only in syllable counting but also in simple perceptual tasks such as length estimation (Chetail & Content, 2014) and letter string discrimination (Chetail, Drabs, et al., 2014). In the length estimation task, letter strings were briefly displayed on the screen and participants had to reproduce the physical length of the items by drawing a line on the screen with the computer mouse. Despite strict matching in objective length on the screen, participants produced shorter lines to represent the length of hiatus words (e.g., oasis) compared to controls words (e.g., opéra). This perceptual bias was interpreted as stemming from the smaller number of orthographic units in hiatus words. The counting and length estimation tasks are nicely complementary. The former offers direct information about the perceived

structure as consciously apprehended by participants. The latter provides an indirect measure of structural effects without directing participants’ attention toward word structure or constituents. Furthermore, because the task does not require identification or access to phonology, it may isolate phenomena related to the earliest stages of orthographic processing. With both techniques, it has been shown that the effects were due to orthographic characteristics and not to phonology. We compared two kinds of hiatus words that include two adjacent vowels in their pronunciation. In one set the phonological hiatus corresponded to adjacent vowel letters, as in chaos (/ka.o/), while in the other set, the two vowels were separated by a silent consonant (e.g., bahut, /ba.y/). Consistent with the CV pattern hypothesis, only the former led to underestimation (Chetail & Content, 2012; Chetail & Content, 2014). To ensure that the structure emerging from the organization of vowels and consonants is orthographic in nature, it is necessary to use words for which the number of vowel clusters differs from the number of syllables. In many words, groups of adjacent vowel letters constitute graphemes and map onto single phonemes so that the number of syllables exactly matches the number of vowel clusters (e.g., chasseur, /ʃasœʀ/). However, this is not true for two kinds of words: those that entail a hiatus pattern and those that entail a silent E (e.g., gobelet, /gɔ.ble/, two syllables, but three vowel clusters). According to the CV pattern hypothesis, hiatus words should be parsed into one orthographic unit less than their number of syllables, due to the presence of two adjacent vowel graphemes constituting a single orthographic unit. Conversely, silent E words should comprise one orthographic unit more than their number of syllables since the E vowel letter in the orthographic form (but not in the phonological form) constitutes one supplementary vowel cluster. So far, the most convincing evidence for the CV pattern as a cue for orthographic parsing was reported with hiatus words. The aim of the present study was to test whether the hypothesis also holds for silent E words. In French or English, words including a silent E are very common (e.g., roughly one third of words in French; Chetail, 2014) whereas hiatus words are rather rare (around 5%). The scarcity of the latter may be taken to support the idea that CV pattern effects are somewhat exceptional and restricted to a few (French) words with atypical characteristics (i.e., presence of an infrequent hiatus pattern). A demonstration with silent E words would thus provide stronger evidence. If the CV organization influences the parsing of letter strings, readers should overestimate the number of units or the physical length of words with a silent E compared to control words (Experiment 1). As in the case of hiatus words, a convincing demonstration would require one to ensure that the effects are due to the structure of orthographic and not phonological representations. To that end, counting and length estimation tasks could be run with the auditory version of the same stimuli. However, previous research has demonstrated that orthographic characteristics may influence spoken word processing. In a now classic study, Seidenberg and Tanenhaus (1979) showed that it is easier to judge that words rhyme when they share the same spelling (e.g., tie/pie) than when their spelling diverges (e.g., tie/rye), a result which was later extended to other languages (e.g., Pattamadilok, Morais, Ventura, & Kolinsky, 2007, in French; Ventura, Morais, Pattamadilok, & Kolinsky, 2004 in Portuguese). Evidence of an influence of literacy on spoken word recognition and production has also been demonstrated with silent letters (e.g., Racine, Bürki, & Spinelli, 2014; Racine & Grosjean, 2005; Ranbom & Connine, 2011). In English for example, Ranbom and Connine (2011) reported that listeners find it harder to discriminate between mispronunciations and standard forms when the spelling (e.g., /kæstl/, castle) was

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consistent with the mispronunciation than when it was not (/hæstl/, hassle). Further evidence in French capitalized on the fact that words with E in the first syllable (e.g., cerise) have two spoken variants, depending on the realization of the schwa (full variant: /səʀiz/ vs reduced variant: /sʀiz/). In word-monitoring experiments, adult listeners were faster to recognize full variants than reduced variants, which may stem from the fact that the full variant is consistent with spelling, contrary to the reduced variant (Racine & Grosjean, 2005; Racine et al., 2014). Based on this literature, we therefore expected that adults would show similar biases in the auditory modality to those with printed stimuli. To ensure that the biases are genuinely driven by orthography, the two tasks in the spoken modality were also administered to prereaders, to beginning readers with limited knowledge of spelling, as well as to more advanced children (third grade). In sum, Experiment 1 tested whether CV pattern effects are present for silent E words presented visually. To assess whether the effects are caused by phonological or orthographic knowledge, the same experiment was conducted in the auditory modality with adult participants (Experiment 2) and with young children at three stages of literacy acquisition (Experiment 3). Experiments 1A-1B: Adults – Visual modality In the two first experiments, words including one vowel cluster more than the number of syllables due to the presence of a silent E (e.g., gobelet, /gɔble/) were compared to control words matched on the number of syllables, letters, and phonemes, but which had equal numbers of vowel clusters and syllables (e.g., crémeux, /kʀemø/). In the counting task, we expected an overestimation of number of units in silent E words compared to control ones. Accordingly in the length estimation task, estimates of word length should be larger for silent E words than control ones. It is important to note that there are several classes of words including the letter E in standard French (see also Racine & Grosjean, 2002). In words that comprise an E in the first syllable, the vowel is optionally deleted if the resulting consonant cluster is an acceptable syllable onset (e.g. la cerise, /la.sʀiz/), but it must be pronounced otherwise (la crevette, /la.kʀə.vet/). By contrast, except in certain words in which the resulting consonant clusters would be illicit (for instance, écrevisse, /e.kʀə.vis/), the schwa is obligatorily deleted in words with an E in non-initial syllables (e.g., gobelet, /gɔ.ble/, impureté, /e~.pyʀ.te/). For such words, the dictionary notation of the standard pronunciation does not include the schwa (Trésor de la langue française informatisé, 2016). All silent E words used in the present experiment involve obligatory schwa deletion. Method Participants Respectively 25 and 22 students participated in Experiments 1A and 1B for course credits. All were native speakers of French and reported normal or corrected-to-normal vision. Stimuli A set of 60 bisyllabic French words was selected in Lexique (New, Pallier, Brysbaert, & Ferrand, 2004). None of the 60 words contained a final silent E (see Appendix A for the list of stimuli). Half of the words included an internal silent E (silent E words, e.g., gobelet, /gɔ.ble/), and they were matched to control words (e.g., crémeux, /kʀe.mø/) on lexical frequency, number of letters, number of phonemes, number of vowel letters, and summed bigram frequency (see Table 1). All the words in the silent E set involve obligatory schwa deletion. Sixty monosyllabic words and

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60 trisyllabic words were added as fillers so that the same number of ‘‘1”, ‘‘2”, and ‘‘3” responses would be elicited. Procedure In both tasks, word presentation and response recording were programmed in Matlab with the Psychtoolbox extension (Brainard, 1997). Experiment 1A. Participants had to decide how many parts each word contained (hereafter ‘counting task’). On each trial, a fixation cross was presented for 300 ms in the center of the screen, followed by a centered lowercase word which remained on screen until the participant responded. Words were displayed in Courier New font. Participants had to decide as quickly and as accurately as possible whether the target word had one, two, or three parts. The experimenter gave an example and the answer orally (‘‘In /matẽ/ (matin) for example, you would say that there are two parts, /ma/ and /tẽ/”). We asked to count ‘‘parts” instead of ‘‘syllables” because we anticipated that the concept of syllable might be unfamiliar to young children (see Experiment 3). Participants responded by pressing one of three contiguous keys on the keyboard with the three central fingers of their dominant hand. The index finger was used to respond one, the middle finger two, and the ring finger three. They performed 10 practice trials (similar to the experimental words) before receiving the 180 trials in a variable random order. No feedback on accuracy was provided. Experiment 1B. Participants performed a length estimation task. On each trial, a fixation cross appeared for 500 ms, immediately followed by a 33 ms mask. The stimulus was then presented during 100 ms followed again by the mask during 33 ms. Words were displayed in lowercase using the Courier New fixed-width font. After the mask, the mouse cursor appeared on the screen and participants had to draw a line representing the physical length of the stimulus. They used the mouse to lengthen or shorten the line and clicked to validate their estimation. Length estimates were recorded in pixels and transformed in character units. In this task too, participants received 10 practice items before the 180 trials in a variable random order. In the practice trials only, feedback indicated how much (in percentage) the estimate differed from the real length. Results Experiment 1A: Counting task Overall, the participants performed correctly, assigning on average fewer parts to shorter words (96% of responses ‘1’ for monosyllabic words, 55% of responses ‘2’ for bisyllabic words, and 95% of responses ‘3’ for trisyllabic words). The mean reaction time was 951 ms (SE = 92 ms). Reaction times were not analysed due to the limited number of trials in some of the conditions. Nevertheless, a few trials for which reaction times were extremely long (>5000 ms) were removed from the analyses (0.09%). Following the analyses conducted by Chetail and Content (2012; see also Chetail, Scaltritti, et al., 2014; Chetail et al., 2016), the proportion of two-part responses in bisyllabic words was submitted to separate analyses of variance across participants (F1) and items (F2) as a function of word type (silent E, control)1. The distribution of responses is presented in Fig. 1. Far fewer two-part responses were given to silent E words than to control words, F1(1, 24) = 169.09, p < .001, F2(1, 58) = 2,436.10, p < .001. Moreover, an analysis of deviant responses (one-part and three-parts responses) showed that par1 Because in some cases the distribution of responses diverged from the normal, we also ran ANOVAs on arcsine-transformed scores. All analyses led to identical conclusions.

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Table 1 Characteristics of words in Experiments 1 and 2. Experimental bisyllabic words

Example Number Lexical frequency (Lexique) Number of letters Number of phonemes Number of vowel letters Summed bigram frequency Duration of pronunciation (ms)

Fillers

Silent E

Control

Monosyllabic

Trisyllabic

gobelet 30 21.11 7.13 4.93 3.27 17,106 671

crémeux 30 29.68 7.13 4.87 3.07 17,887 700

Film 60 21.11 4.67 3.47 1.68 18,593 603

restaurant 60 29.68 9.00 6.85 3.67 11,567 794

Notes. Frequencies are in number of occurrences per millions. Bigram frequencies were computed on Lexique (New et al., 2004)

b = 0.28, t = model.

Proportion of responses (%)

100

3.38, p = .001, significantly contributed to the final

Discussion 75

1 part 2 parts 3 parts

50

25

0 Control

Silent E

Type of bisyllabic words Fig. 1. Proportion of responses 1, 2, 3 according to the type of bisyllabic words in Experiment 1A. Error bars represent standard errors.

ticipants produced many more three-part than one-part responses in silent E words, t(24) = 14.42, p < .001, while no such effect was found in control words, t(24) = 0.67, p = .51. Accordingly, the interaction between the type of words and the type of deviant responses was significant, F(1, 24) = 279.10, p < .001.

As expected, two-part responses were more often attributed to control words than to silent E words in the counting task, and silent E words were massively treated as comprising three parts, corresponding to the number of vowel clusters rather than to the number of phonological syllables. Consistently, silent E words were estimated to be longer than control words, despite being exactly the same length on screen. This suggests that participants determined orthographic units based on the CV pattern rather than on syllable structure. These results are in line with previous experiments on hiatus words (Chetail & Content, 2012; Chetail & Content, 2014) showing underestimation of both number of units and physical length in comparison to control words. We assume that the two opposite patterns stem from the same process. The underestimation bias was explained by the orthographic structure of hiatus words, which comprise two distinct but adjacent vowel graphemes (e.g., reunion), leading to one orthographic vowel cluster less than the corresponding control words. Here, the overestimation is presumably due to the presence of a silent E which constitutes an additional vowel cluster.2 Experiments 2A-2B: Adults – Auditory modality

Experiment 1B: Length estimation task The same analyses as in Chetail and Content (2014) were conducted since the present experiment used the same design. Extreme values deviating from the real length by 90% or more were discarded from the analyses (0.20%). Overall, the estimated length was close to the real length (85 vs. 89 pixels respectively for monosyllabic items, 141 vs. 136 for bisyllabic items, and 173 vs. 171 for trisyllabic items). We fitted a linear mixed-effect regression model using the lme4 package in the R software (Baayen, Davidson, & Bates, 2008) on the estimates for bisyllabic silent E and control items. The model included word type (silent E, control) as a fixed factor, and random intercepts for both participants and items. As words varied overall in number of letters, length in letters was added as a covariate. In addition, given that most of the time readers are exposed to words written in proportional fonts and might thus rely on a memory representation incorporating letter size variations (e.g., the fact that ‘w’ takes more space than ‘i’), we also included a proportionality correction as a covariate (see Chetail & Content, 2014). The two covariates were centered. A significant word type effect was found, silent E words being estimated longer than control words (144 vs. 138 pixels respectively, corresponding to 7.56 vs. 7.27 characters on the screen), b = 5.30, t = 3.11, p = .003. The two covariates, letter length, b = 0.99, t = 15.83, p < .001, and proportionality correction,

In Experiment 2, we transposed the two tasks used in Experiment 1 to the auditory modality. For the counting task, spoken words were presented and adult participants had to decide how many parts they contained. For the length estimation task, the stimuli were also presented auditorily and participants had to estimate the duration of pronunciation (instead of the physical extent on the screen). Based on previous studies (e.g., Racine & Grosjean, 2005; Racine et al., 2014; Ranbom & Connine, 2011), we expected to find similar biases with spoken and written materials. The silent E words were produced with the standard pronunciation (i.e., without the schwa) and they had on average the same duration as the control words (as well as identical number of syllables). Method Participants Respectively 25 and 23 new students participated in Experiments 2A and 2B. They were all native French speakers. 2 It seems unlikely that this effect can be ascribed to vagueness in the instructions (counting ‘‘parts”). First, the results for the filler words show that the participants unanimously counted coarse units akin to syllables. Second, a preliminary study conducted years ago with a paper-and-pencil design directly compared the influence of instructions in unit counting and showed no increase of the effect in the ‘‘parts” instructions (see Appendix B).

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Stimuli The same words as in Experiment 1 were used. They were recorded by a male native French speaker with the Praat software (Boersma, 2001). Silent E words and control words were matched on mean duration of pronunciation (Table 1). Procedure The procedure of Experiments 2A and 2B was the same as in Experiments 1A and 1B respectively, except that words were presented auditorily instead of visually. In the counting task (Experiment 2A), participants had to decide whether the spoken words had one, two, or three parts. In the length estimation task (Experiment 2B), they had to draw a line representing the duration of the stimulus. No feedback was provided in either task. After the main task, participants performed a spelling test to ensure that they knew the correct spelling of the items. The spelling test included the 60 experimental words plus 10 fillers. Results Experiment 2A Spelling test. The average accuracy for the spelling test was 90% altogether. Most of the errors corresponded to inaccurate final silent letters (e.g., matelat instead of matelas) or geminate consonants (lotterie instead of loterie). The accuracy was similar for control and silent E words (88% in both condition). Only 3% of errors in silent E words were due to the omission of the silent E. In the following analyses, we removed for each participant the words for which they omitted the silent E. Counting task. The participants performed adequately, assigning on average fewer parts to shorter words (91% of responses ‘1’ for monosyllabic words, 59% of responses ‘2’ for bisyllabic words, and 98% of responses ‘3’ for trisyllabic words). A few trials for which reaction times were extremely long (>5000 ms) were removed from the analyses (0.09%). The mean reaction time was 1225 ms (SE = 95 ms). The distribution of responses for bisyllabic silent E words and controls is presented in Fig. 2. We ran similar ANOVAs as in Experiment 1A. Silent E words produced far fewer two-part responses than control words, F1(1, 24) = 305.78, p < .001, F2(1, 58) = 493.47, p < .001. An analysis of deviant responses for silent E words showed that participants gave more three-part than one-part responses, t(24) = 18.35, p < .001. This was also the case for control words, t(24) = 4.04, p < .001, but the interaction showed that the effect was much stronger in silent E words than in controls, F(1, 24) = 329.50, p < .001.

Proportion of responses (%)

100

75

1 part 2 parts 3 parts

50

25

0 Control

Silent E

Type of bisyllabic words Fig. 2. Proportion of responses 1, 2, 3 according to the type of bisyllabic words in Experiment 2A. Error bars represent standard errors.

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Experiment 2B Spelling test. The average accuracy was 93%. The accuracy was similar for controls and silent E words (92 and 90 respectively). Only 2% of errors in silent E words corresponded to omissions of the E. In the following analyses, words erroneously spelt without the silent E were removed. Length estimation task. Extreme values inferior to 10 pixels were discarded (0.82%). Overall, the estimated length was compatible with the duration of the pronunciation (75, 144, and 180 pixels for mono-, bi-, and tri-syllabic items respectively). We ran similar mixed-model analyses as in Experiment 1B on the estimates for bisyllabic silent E and control items, except that the duration of pronunciation (in ms) was used as covariate instead of the length in letters, and that the proportionality correction was not used. A significant word type effect was found, silent E words being estimated longer than control words (154 vs. 133 pixels respectively), b = 21.20, t = 5.55, p < .001. The effect of duration of pronunciation was marginally significant, b = 0.03, t = 1.74, p = .083.

Discussion Although the silent E and control words had exactly the same number of syllables, the same number of phonemes, and were matched on duration of pronunciation, participants often attributed one more unit to silent E words than to control words (Experiment 2A) and they estimated the silent E words longer than the control words (Experiment 2B).4 In the perceptual task, the bias produced by the silent E was stronger for spoken than for written words, as shown by a comparison between Experiment 1B and 2B, F(1, 43) = 7.61, p = .009. We hypothesize that this is because in the written modality, estimates are more directly constrained by the physical reality than with auditory stimuli, as there is a more direct mapping between the stimuli and response. One could argue that the presence of similar biases with auditory and printed stimuli suggests that the overestimation effect found in both experiments derives from phonology. More specifically, given that participants often rely on subvocal pronunciation in the counting task (Chetail & Content, 2012), it could be the case that silent E words evoke a phonological variant in which the E is realized, even though we took care to select words with obligatory schwa deletion. If so, the effects found in the two experiments would stem from the presence of three syllabic units in the phonological form and not from the presence of three orthographic vowel clusters. However, as already underlined in the introduction, previous research has demonstrated that orthographic characteristics may influence spoken word processing. Hence, the overestimation effects in the auditory modality could also arise from the activation of orthographic information. Experiment 3 was designed to test this proposal, by examining the counting and estimation performance of young children with spoken words. If the effects found in Experiment 2 are caused by the orthographic structure, then they should not be present in participants who do not know the spelling of silent E words. 3 When the orthographic covariates used in Experiment 1B were introduced in the model (i.e., number of letters and proportionality correction), the results remained similar (a significant effect of word type and no significant effect of duration of pronunciation), but the number of letters additionally contributed to length estimation (b = 16.56, t = 11.16, p < .001). 4 In the pilot experiment described in footnote 1, we also tested the effect of instructions (‘‘parts” vs. ‘‘syllables”) with auditory stimuli. Again, a higher proportion of two-part responses in silent E words than in control words was observed, whatever the instructions (see Appendix B).

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Experiments 3A-3B: Children – Auditory modality In the final pair of experiments, the same effects as in Experiment 2 were tested in prereaders and children who were at the beginning of reading instruction and who therefore knew little about the spelling of the stimulus words (as attested by a spelling test). Testing whether a given manipulation on spoken words fails to produce the same effect with preliterate subjects as with skilled readers provides an elegant way to demonstrate the orthographic origin of the effect (see e.g., Racine et al., 2014; Ventura et al., 2004; Ziegler & Muneaux, 2007). We tested three groups of children, varying in spelling knowledge (kindergarteners, first graders, and third graders). If the effects found in Experiment 2 with literate adults were due to orthographic structure, no significant difference between the two sets of words should come out in prereaders or beginners, and third-graders should produce effects smaller than adults who know the spelling of the experimental words5. Method Participants In Experiment 3A, respectively 24, 23, and 28 children in kindergarten, grade 1, and grade 3 participated. In Experiment 3B, there were 24, 22, and 26 children respectively. The mean age in the three groups of age was 5;6, 6;3, and 8;10 years. All children were native French speakers. Kindergarteners were tested at mid-year and were not able to spell any word. First graders were tested three or four months after the beginning of the year and had only rudimentary reading and spelling skill. Third-graders were tested four or five months after the beginning of the year, and had more substantial reading and spelling skills. Stimuli Only half of the items from previous experiments, namely the most frequent ones (see Appendix C) were used, in order to limit the duration of the tests. In this subset, silent E and control words were matched on the same variables as in adults (see Table 2), the difference being that lexical frequency was taken from the Manulex database, which is specific to elementary school readers (Lété, Sprenger-Charolles, & Colé, 2004). Similarly, half of the fillers were selected among those used in Experiments 1And 2 so that the same number of one-part, two-part and three-part responses should be elicited. The same audio files as in Experiment 2 were used. The remaining pools of silent E and control words were matched on the duration of pronunciation. Procedure The procedure for Experiments 3A and 3B was the same as in Experiments 2A and 2B, except that the children received a short warm-up prior to the experiment proper. In the unit-counting task, the experimenter said single words and asked the children to count the number of parts. In the duration estimation task, the experimenter played a beep and asked the children to draw a line on a sheet of paper to represent the duration of the sound. In both warm-ups, the participants were presented with short, medium, and long stimuli, and the experimenter cheered them and ensured that they understood the task. After the training, the children were told that they would perform the same game on a computer, except that they would not give their responses out loud or on paper, but by means of the keyboard or the mouse. The session started with the 10 practice trials on the computer, followed by the 90 experimental trials. In the count5 Initially, we tested only first graders at the beginning of the first school year. Following reviewers’ comments, we added kindergarteners and more advanced children in third grade.

ing task, many children did not maintain their fingers on the keys during the entire experiment and responded just with the forefinger. After the main task, the children in grade 1And grade 3 received a spelling test to examine whether they knew the correct spelling of the silent E words. The test included the 30 experimental words plus 10 highly familiar fillers. The spelling test was run collectively in the classroom. Two children in grade 1 (one in each experiment) and four children in grade 3 (two in each experiment) were absent for the spelling test. Kindergarteners were tested individually to evaluate whether they were able to spell four easy words (papa, daddy; bébé, baby; vache, cow; classe, class). If so, they would receive the full test. Results Experiment 3A Spelling test. None of the kindergarteners was able to spell even the two easiest words papa and bébé (even in a phonological plausible way), so none of them received the spelling test. This confirmed that they had virtually no knowledge of word spelling. In grade 1, the spelling profile strongly varied across children (Fig. 3). A few were able to write almost all the words whereas others had trouble writing even the most common fillers. Most of the time, they produced spellings that were phonetically consistent with the pronunciation. On average, they spelled 46% of the filler words perfectly (ranging from 10 to 100%), but the experimental words were often misspelled (5% of correct responses). More importantly, the silent E was present in the spelling of silent E words in only 13% of the cases, due to the frequent correct spelling of the word samedi (Saturday, 76% correct) and to two children who showed advanced spelling skills and who included the silent E in many items (60 and 73%). When the word samedi and these two children were excluded, the percentage of silent E word spelling including the silent E fell to 3%. This item and the two children were removed from the following analyses, as well as the few remaining trials for which a silent E word was written with the silent E. In grade 3, the children spelled 86% of the filler words perfectly (scores ranging from 50 to 100%) and 26% of the experimental words (26% for control words, 26% for silent E words). Many errors were phonetically plausible. The low accuracy is likely due to lack of familiarity, as many stimuli are supposed to be acquired even later than grade 5 (e.g., matelas: 32% of accuracy in grade 5, parquet: 56%, aspect: 31%, gobelet: 27%, see Pothier & Pothier, 2002). The critical point of the spelling task was to determine whether children did or did not include the silent E in the experimental words. The E was present in 55% of silent E words (ranging from 13 to 100% among children), with some words being almost systematically spelled with E (e.g., avenir, avenue, galerie, samedi, souvenir, vêtement). Given that roughly half of the spelled words included the E, all responses were used in the analyses and we thus expected a pattern of results intermediate between first graders and adults. Counting task. One kindergartener was excluded because he did not understand the instructions. Trials with very long (>10,000 ms) or short (<300 ms) response times were removed from the analyses (3.70%, 1.40%, 1.23% of the data for kindergarten, grade 1And grade 3 respectively). Overall, in the three age groups, the participants performed adequately, assigning on average fewer parts to shorter words (see Table 3). The distributions of responses for bisyllabic words as a function of group and word set are presented in Fig. 4. The proportion of two-part responses was submitted to separate analyses of variance on the participant means (F1) and on the item means (F2) as a function of word type (silent E, control)

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F. Chetail, A. Content / Journal of Memory and Language 97 (2017) 121–134 Table 2 Characteristics of words in Experiment 3. Experimental bisyllabic words

Example Number Lexical frequency (Manulex) Number of letters Number of phonemes Number of vowels Summed bigram frequency Duration of pronunciation (ms)

Fillers

Silent E

Control

Monosyllabic

Trisyllabic

gobelet 15 45.91 6.93 4.93 3.27 17,071 683

crémeux 15 45.20 6.93 4.87 3.00 18,769 681

film 30 87.14 4.47 3.20 1.73 13,529 581

restaurant 30 47.09 8.97 6.77 3.57 19,379 765

Note. Bigram frequencies were computed on Lexique (New et al., 2004, in number of occurrences per million).

Fig. 3. Spelling responses of 6 children in grade 1 for 8 words (top-to-down for each column: classe, samedi, rouge, charbon, costaud, citron, vêtement, parquet).

and group (kindergarten, grade 1, grade 3). There was a significant interaction between the two factors, F1(2, 70) = 24.48, p < .001, F2(2, 54) = 20.43, p < .001. We therefore analysed the proportion of two-part responses as a function of word type (silent E, control) for each group. As previously, we also analysed the proportion of deviant responses (1 part, 3 parts) for the critical bisyllabic words. In kindergarten, there was no significant difference between the proportion of two-part responses for silent E words and control words, F1(1, 23) = 2.19, p = .15, F2(1, 28) = 2.39, p =.13. An analysis on deviant responses showed that overall participants gave slightly more three-part than one-part responses in both silent E words,

t(23) = 2.13, p = .04, and control words, t(23) = 1.97, p = .06, but there was no difference between silent E and control words, F(1, 23) = 1.26, p = .27. Table 3 Proportion of expected responses according to number of syllables and group..

Kindergarten Grade 1 Grade 3

Response ‘1’ for monosyllabic words

Response ‘2’ for bisyllabic words

Response ‘3’ for trisyllabic words

80 83 65

81 91 51

89 97 95

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Grade 1

Grade 3

100

100

100

75

75

75

50

50

25

25

0

prop

Proportion of responses (%)

Kindergarten

Silent E

Type of bisyllabic words

50

25

0 Control

1 part 2 parts 3 parts

0 Control

Silent E

Type of bisyllabic words

Control

Silent E

Type of bisyllabic words

Fig. 4. Proportion of 1, 2, 3 parts responses according to word type and group (Experiment 3A). Error bars represent standard errors.

In grade 1, there was no significant difference between the proportion of two-part responses for silent E words and control words, F1(1, 20) = 2.64, p = .12, F2(1, 27) = 3.27, p =.08. The analysis on deviant responses showed that overall participants gave slightly more three-part than one-part responses for silent E words, t(20) = 2.95, p = 0.008, whereas this effect was not present in control words, t(20) = 1.05, p = 0.31. Accordingly, the interaction between the type of words and the type of responses was significant, F(1 ,20) = 10.38, p = .004. Given that this difference is not present in kindergarten, this slight difference may reflect minimal knowledge of silent E word spelling, despite the fact that the few items for which they explicitly included a silent E in the spelling test were removed. As suggested by an anonymous reviewer, residual orthographic knowledge insufficiently strong to surface in spelling might still leave a trace in counting behaviour. In grade 3, silent E words produced fewer two-part responses than control words, F1(1, 27) = 59.54, p < .001, F2(1, 28) = 32.58, p < .001. The analysis on deviant responses showed that overall participants gave more three-part than one-part responses for both silent E words, t(27) = -12.96, p < .001, and control words, t(27)=-5.20, p < .001, but this trend was stronger for silent E words, F(1, 27) = 53.77, p < .001.

Experiment 3B Spelling test. None of the kindergarteners was able to spell the four easy words. In grade 1, the spelling profile strongly varied across children as in Experiment 3A. On average, they spelled 42% of the filler words perfectly (scores ranging from 10% to 80%), and they misspelled most of the experimental words (12% of correct responses). The E was present in 12% of the cases. Here again, the correct spellings were largely due to the word samedi (91% of the cases). When it was removed, the percentage of silent E word spelling including the silent E fell to 3%. This item was removed from the following analyses, as well as the few remaining trials for which a silent E word was written with the silent E. Thirdgraders spelled 85% of the filler words perfectly (from 40% to 100%) and 19% of the experimental words (20% for control words, 19% for silent E words). The E was present in 48% of silent E words (ranging from 20% to 93% among children). As in Experiment 3A, no words were excluded for this group. Length estimation task. One kindergartener was excluded because he did not understand the instructions. Trials with extreme values (inferior to 10 pixels) were discarded (6.97%, 2.20%, and 1.50% in kindergarten, grade 1, and grade 3 respectively). Overall, the estimated length increased with the duration

of word pronunciation (Table 4). We ran similar mixed-model analyses as in Experiment 2B on the estimates for bisyllabic items, with word type (silent E, control words) and group (kindergarten, grade 1, grade 3) as fixed factors. The effect of group was significant, reflecting the large difference between kindergarteners and other groups [kindergarten vs. grade 1, b = -178.18, t = -5.19, p < .001; kindergarten vs. grade 3, b = -113.11, t = -3.32, p = .001], but neither the effect of word type nor the interaction approached significance (all ps > .38). Separate analyses for each group indicated that the length estimation task was more difficult to apprehend for younger children. In neither of the three groups did the duration of pronunciation significantly contribute to predict performance (all ps > .47). Furthermore, the word type effect failed to reach significance in kindergarten (b = 0.97, t = 0.06, p = .96), grade 1 (b = -13.05, t = 1.73, p = .09), and grade 3 (b = 11.62 t = 1.50, p = .14). As some children (especially kindergarteners) gave aberrant responses (e.g., a very long line for train), we ran further analyses with subsets of children for whom we had an indication that they performed properly. Children were selected according to whether their estimates exhibited a significant correlation with either the real duration, the number of syllables, or the number of phonemes of the stimuli. In neither subset was there any hint of a difference in length estimation according to word type (all ps > .24, with 5–7 kindergarteners per subset; 11–13 first graders; 18–19 third graders). Discussion In the counting task, there was no difference in the proportion of correct responses between silent E and control words for prereaders and first-graders. By contrast, for children in grade 3 who knew the spelling of a substantial number of silent E words, a clear bias was found, and more three-part responses were assigned to bisyllabic silent E words than to bisyllabic control words6. In the duration estimation task, while kindergarteners and firstgraders showed no effect, a difference between the two types of words in the predicted direction was found in third graders, but it clearly failed to reach significance. One possible explanation is that third-graders orthographic knowledge was not sufficient, or sufficiently strong, to influence duration estimations in a consis6 Third-graders also tended to overestimate the number of parts with monosyllabic fillers and bisyllabic control items. One potential explanation –which would require further examination– is that they sometimes respond on the basis of finer grain units (e.g., graphemes).

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Table 4 Estimated length according to number of syllables, and type of bisyllabic words (right) for the three age groups of children (Experiment 3B) and for adults (Experiment 2B). All items

Kindergarten Grade 1 Grade 3 Adults

Bisyllabic words

Monosyllabic

Bisyllabic

Trisyllabic

Silent E

Controls

308 127 153 75

320 158 195 144

339 193 212 180

320 152 200 154

319 165 189 133

tent way. Another possibility is that the duration bias requires more literacy expertise to emerge. General discussion The present results provide converging evidence that the organization of consonant and vowel letters, which we labelled the CV pattern, determines the structure of one salient level of orthographic representation. Words equated on their number of syllables, phonemes, and letters are not considered to be equally long if the number of orthographic units determined by their CV pattern is not identical too. Here, we showed that adult participants judged that printed words including a silent E comprise more units (Experiment 1A) and are spatially longer (Experiment 1B) than control words precisely matched in length and number of syllables. These biases were also present when the same words were presented auditorily (Experiments 2A-2B). On the contrary, beginning readers who had no knowledge of the spelling of the words showed no similar biases (Experiments 3A-3B). Although bisyllabic words served as stimuli in the present study, there is no reason to believe that the observed effects should be restricted to bisyllabic items. In French (as in other languages), many monosyllabic words end with a silent E (e.g., rouge, plante, graine) and would be structured into two orthographic units. In the following, we first discuss the interpretation of the effects observed in the auditory modality, and then return to the main issue of orthographic parsing. CV pattern effects in the auditory modality The results in the auditory modality conform to the hypothesis of an orthographic origin of the effects: the silent E manipulation in bisyllabic words had an effect only in readers who reliably knew the spelling of words with and without a silent E (Experiment 2 vs. 3). However, an alternative interpretation assuming the existence of full variant lexical representations (e.g., /gɔ.bə.le/) requires examination. Several recent studies actually suggest that distinct phonological forms are stored in the lexicon for schwa words, one for the reduced variant and one for the full variant. Bürki, Ernestus and Frauenfelder (2010) used a picture naming task to elicit both the full and reduced variant for words including a schwa in the first syllable (e.g., fenêtre, /fənetʀ/ realized as [fənetʀ] or [fnetʀ], respectively). They argued that both variants must be represented in the lexicon because the naming latencies were affected by the relative frequency of the two variants. Later experiments (Bürki, Alario, & Frauenfelder, 2011) extended these observations with words similar to those used in the present study (obligatory deletion words, such as gobelet) and showed that both variants provoke pseudohomophone facilitation effects (e.g., facilitation for pseudowords homophones of both the full variant, e.g., gobeulait, and the reduced variant, e.g., goblait). This was true even for variants that are uncommon in the subjects’ regional dialect, provided these variants are either familiar (due to encounters with other accents) or consistent with the spelling of the word. Finally, Bürki, Spinelli, and Gaskell (2012) had participants learn novel auditory forms for

pictures of unfamiliar objects and reported that a single exposure to a spelling with an E was sufficient to induce the production of spoken variants including the schwa. Hence, even if listeners were only rarely exposed to the full variant of the silent E words used in the present experiments, there is evidence that both the reduced variant and the full phonological variant may be part of their phonological knowledge. As a consequence, one could wonder whether the effects obtained here in the auditory modality could be caused by the activation of lexical representations including the schwa phoneme (e.g., /gɔ.bə.le/). If this purely phonological account was correct, silent E words would elicit three-part responses in the present auditory tasks not because they are orthographically structured into three orthographic units, but because listeners evoke the phonological representation of the full variant. It is however unclear why the existence of the full variant in the phonological lexicon would prevail over the information provided by the input itself. This seems even more implausible given that the input corresponds by far to the most frequent variant. Indeed, the work of Racine and collaborators with obligatory deletion words provides no evidence for an advantage of the full variant. Racine and Grosjean (2005) used a shadowing task and a lexical decision task in adults and reported no response time differences between full and reduced variants. Similarly in a word detection task, Racine et al. (2014) found no difference between full and reduced variants in third graders, whereas prereaders were faster with the reduced variant. According to the authors, the faster recognition of reduced variants in prereaders is due to the fact that these forms are much more frequent in the language. By contrast, in readers, the frequency advantage of reduced variants would be counterbalanced by the full variant compatibility with spelling, leading to a null effect. Moreover, even the prereaders were able to identify words from their full variant, suggesting that they too were somewhat acquainted with both forms. Hence, a pure phonological explanation based on the existence of full variant representations would not predict the developmental results obtained in Experiment 3. In sum, although there is evidence to support the existence of full variants for silent E words in lexical memory, it does not explain the massive preference for counting responses corresponding to the full variant, nor the absence of overestimation effects in prereaders. A more plausible way to account for the biases in the auditory modality is to hypothesize that it finds its origin in orthographic knowledge. In line with various sources of empirical evidence (e.g., Pattamadilok et al., 2007; Ranbom & Connine, 2011; Seidenberg & Tanenhaus, 1979; Ventura et al., 2004), several current models assume that the activation of a phonological representation by spoken input quickly flows to the representation of its orthographic counterpart (e.g., Ferrand & Grainger, 1994; Ziegler, Rey, & Jacobs, 1998). In these models, separate sets of units for whole word phonological and orthographic forms are interconnected by excitatory connections. Each level in turn feeds back to a layer of sublexical units. When a phonological word form is activated by the auditory input, activation automatically flows to the orthographic word form, and then down to sublexical levels of orthographic units. In adults, activation at the level of sublexical

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orthographic units may be strong enough to influence responses to spoken stimuli, and even more so if the orthographic sublexical structure directly maps onto the phonological sublexical structure, as would be the case between orthography and the full phonological variant. On the contrary, readers with limited spelling knowledge (kindergarteners and first graders) would rely on phonological information (and perhaps also on partial orthographic coding). In that case, no bias would emerge. CV pattern effects in the written modality The orthographic interpretation of the effects in the auditory modality is in line with the results obtained in the visual modality, showing that bisyllabic words including a silent E were judged as including more units and being longer than control words matched in length. Critically, this is convergent with previous studies on hiatus words conducted with the syllable counting and the length estimation tasks (Chetail & Content, 2012; Chetail & Content, 2014). Words like gobelet are perceived as composed of three orthographic units, consistent with an orthographic description, rather than two, as would be predicted based on the syllabic structure of the most frequent variant (i.e., /gɔ.ble/). Even acknowledging the existence of the full phonological variant would not easily account for the massive preference for three-part responses and for the clear-cut overestimation of length shown in Experiment 1. However, it could explain why the effect in the counting task is stronger than what was previously reported with hiatus words (effect of 78 percentage points in Experiment 1A; 12 points in Chetail & Content, 2012; 20 points in Chetail, Scaltritti, et al., 2014). Indeed, in silent E words, the parsing in three units based on the CV pattern is compatible with the structure of the full variant and this might reinforce the effect. No such compatibility exists for hiatus words (i.e., there is no monosyllabic phonological variant for chaos in French that maps onto its one vowel-cluster orthographic structure). The fact that a stronger effect was found in the counting task for silent E words compared to hiatus words suggests that it can be reinforced when phonological information is recruited and consistent with the orthographic structure. This is not surprising as previous findings showed that adults rely on phonology in the syllable counting task (Chetail & Content, 2012). By contrast, the observation that similar length estimation biases were found when the orthographic structure induced one unit less (hiatus) and one unit more (silent E) confirms our previous claim that the origin of the bias is orthographic in nature. A limit of previous studies was that the evidence for CV pattern effects came from experiments conducted with a restricted set of words exhibiting an atypical phonemic pattern, namely hiatus words. The goal of the present study was to test whether the effects were limited to such words or were more general. The replication of the results in the counting and length estimation tasks with silent E words here demonstrates that the influence of the CV pattern is not restricted to a small atypical class of stimuli such as hiatus words but extends to common and broadly represented items such as silent E words. Assumptions about tasks Given the nature of the tasks used in the present study, one may wonder whether the effects reported inform our understanding of visual word recognition. In the counting task for instance, does the effect emerge because the CV structure exists in the word recognition system or is it due to late decision strategies? The counting task requires an explicit judgment about the perceived structure of letter strings as consciously apprehended. Length estimation focuses upon a physical characteristic of the stimuli and indirectly reveals the influence of the perceptual structure, without ever call-

ing attention to units, parts or parsing mechanisms. None of the tasks requires word identification nor access to word meaning. Tasks requiring a voluntary judgment on stimulus characteristics are commonly used in psycholinguistic research, and most of the time, they produce results convergent with other techniques. For instance Seidenberg and Tanenhaus (1979) used rhyme judgments to demonstrate the impact of orthography on spoken word recognition, and their conclusion was confirmed with other techniques such as shadowing, lexical decision as well as event related potentials (ERPs, e.g., Pattamadilok, Perre, Dufau, & Ziegler, 2009; Petrova, Gaskell, & Ferrand, 2011; Ventura et al., 2004; Ziegler & Ferrand, 1998). A similar point applies to perceptual tasks devised to investigate functional units in written word processing. For instance, Prinzmetal et al. (1986) used color judgments, assuming that illusory conjunction errors reveal the influence of word structure. Again, their findings were confirmed in lexical decision, naming, as well as ERP studies (e.g., Alvarez et al., 2004; Carreiras et al., 1993; Chetail, Colin, & Content, 2012; Conrad & Jacobs, 2004). Nevertheless, how the tasks used in the present study relate to visual word recognition needs to be clarified. We argue that several strands of evidence support the view that the phenomena observed here are based on a read-out of information extracted during early automatic processing stages and thus reflect the perceptual structure of letter strings. In French, response time differences were obtained between long polysyllabic hiatus and control words both in lexical decision and naming (Chetail & Content, 2012). We proposed to account for the observed pattern by a combination of two elements; the smaller number of vowel-cluster units in hiatus words which could shorten processing, and the potential conflict between orthographic and phonological structures which fail to match in the case of hiatus words (e.g., client: one orthographic unit; /klaɪ.ənt/: 2 syllables). Analyses on megastudy corpuses in English led to similar conclusions (Chetail, Balota, Treiman, & Content, 2015). Another series of experiments used the cross-case sequential matching task in which participants have to decide whether two letter strings are identical or different. The task is particularly suited to examine early visuo-orthographic processes (e.g., Duñabeitia, Dimitropoulou, Grainger, Hernández, & Carreiras, 2012; Kinoshita & Norris, 2009). Chetail, Drabs, et al. (2014) showed that mismatches were more rapidly detected when the target and the referent differed in orthographic structure (e.g., BOUDLET / bodulet 2 vs. 3 vowel clusters) than when they shared the same structure (e.g., FOUREIL / forueil, 2 vowel clusters). Finally, Chetail (2014) proposed that the number of vowelcluster units rather than the number of syllables is a relevant dimension to account for reaction times in lexical decision. This was supported both by the absence of difference between bisyllabic silent E words (e.g., valise, /va.liz/) and trisyllabic non-silent E items (e.g., vanité, /va.ni.te/), and by the slower processing of words with a silent E (e.g., biberon, /bi.bʀõ/) compared to controls (e.g., nombril, /nõ.bʀil/). The results in the counting task of the present study further validate this interpretation by showing that participants indeed assign one more orthographic unit to silent E words than to controls. In sum, findings obtained in unit counting and length estimation tasks converge with those reported in more typical word recognition tasks, justifying the claim that the kind of information about structure which influences performance in the former tasks is also involved in visual word recognition. Implications for visual word recognition processes Within a general interactive activation framework, we consider that letter strings are processed in a complex hierarchy

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of simultaneously active detectors, each one being responsible for the coding of a certain element of information, from the simplest sensory properties to more abstract and composite characteristics (e.g., Dehaene et al., 2005; McClelland & Rumelhart, 1981). In this framework, one level in the hierarchy is assumed to be shaped by the CV pattern, so that higher-order elements in the hierarchy –which we label vowel-centered units–, correspond to groups of contiguous letters, centered on a vowel or vowel cluster. Once enough information is captured by the perceptual system, activation would flow from letter feature nodes to vowel cluster nodes and then to word nodes (Chetail, Drabs, et al., 2014). The activation at the level of vowel cluster units is assumed to provide precise information on the number of large sublexical units and can be used to read out a gross measure of word length. This length-sensitive mechanism would code the orthographic structure of letter strings according to a definite and fixed scheme, independently of grapho-phonological mapping. In French, for example, the E in atelier and cadenas would be the kernel of an orthographic unit whether it has a direct phonological counterpart (as in atelier, /atəlje/) or not (as in cadenas, /kadna/). Given the requirements of the counting and length estimation tasks (i.e., quickly extract a rough estimate of letter string length), the activation at the vowel cluster units would be instrumental in explaining the performance (assignment of three units to bisyllabic silent E words despite a phonological structure in two units, and larger length estimation compared to regular bisyllabic words). More generally, this length sensitive mechanism could also play a critical role in visual word recognition to constrain the activation of the potential competitor pool for word recognition, so that only candidates with the appropriate structure would be activated (Chetail & Mathey, 2011; Smith, Jordan, & Sharma, 1991). The vowel cluster hypothesis is compatible with the existence of smaller units such as letters or graphemes (see Chetail, Drabs, et al., 2014 for a discussion) in the processing system. On the other hand, it seems hard to reconcile with hypotheses assuming larger orthographic units corresponding to graphosyllables or morphemes for example. Regarding graphosyllables (i.e., the orthographic transcription of syllables), although they may often correspond to vowel cluster units (e.g., morning: two vowel clusters and two graphosyllables), data indicate that when they can be distinguished (typically in hiatus or silent E words), the processing of written words is influenced by vowel cluster units rather than by graphosyllables. This led Chetail (2014) to reinterpret syllabic effects in visual word recognition as CV pattern effects. Regarding morphemes, whether vowel cluster units influence for example morphemic priming effects (e.g., Longtin, Segui, & Hallé, 2003; Rastle, Davis, & New, 2004) has never been examined, but results obtained with the syllable counting task suggest that CV pattern effects are independent from morphemic structure (Chetail & Quémart, 2014).

Conclusion Previous studies indicating that the CV pattern underpins the perceptual structure of letter strings could have seemed unconvincing since the stimuli used –hiatus words–, are rare and could be seen as an atypical class of words. We report here a new set of data confirming the CV pattern predictions with a class of words which is much more common in French and in other languages. The CV pattern of printed words influences their perception, and the mere presence of a silent E in letter strings affects the way they are parsed into letter chunks as well as the estimation of their length. Furthermore, we showed that the orthographic structure

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is sufficiently salient to affect spoken word processing in literate persons. Pure phonological accounts do not seem to provide an adequate explanation of the observed bias. Finally, based on the comparison of the different studies carried out to examine CV pattern effects, we showed that these effects are unlikely to be artefacts due to the nature of the tasks, but may reflect the result of early letter string processing. The findings demonstrate that the influence of the CV pattern is not restricted to a specific set of words such as those including a hiatus, and suggest that the organization of consonant and vowel letters constitutes an important characteristic used by the perceptual system. We would thus expect to observe the same effects in alphabetic writing systems with a similar consonant/vowel letter organization.

Authors’ notes The work reported here has been supported in part by the Interuniversity Attraction Poles Program of the Belgian Science Policy Office (Project P7/33). F. Chetail was a postdoctoral researcher for the National Fund for Scientific Research (F.R.S.FNRS) at the time of the study. All the raw data and scripts for analyses are available on Open Science Framework: https:// osf.io/y658a/.

Words used in adults (Experiments 1A, 1B, 2A, 2B) Silent E words sonnerie, saleté, logement, pureté, vêtement, galerie, matelas, samedi, empereur, avenue, allemand, médecin, sûrement, avenir, souvenir, riverain, gisement, bibelot, céleri, laverie, javelot, paquebot, gobelet, cadenas, hameçon, calepin, biberon, matelot, loterie, caleçon

Control words maintien, citron, cueillir, fumier, chanteur, parquet, charbon, alcool, chasseur, aspect, instinct, tableau, fauteuil, hasard, question, pingouin, bourgeon, fugueur, pivert, fenouil, calmant, hargneux, crémeux, méfiant, engrais, suspect, costaud, moisson, vendeur, complot

Fillers chef, neuf, film, gras, mars, fric, ours, miel, chou, clan, clou, gant, golf, pull, foot, vrac, pneu, veuf, pion, grue, boum, cône, rein, troc, droit, blanc, front, soeur, pluie, chaud, lourd, blond, proie, grain, deuil, sourd, plomb, sport, noeud, creux, craie, match, frein, short, clown, flair, gland, stand, groom, groin, steak, preux, scoop, snack, scalp, spray, treuil, sprint, script, sphinx, simplement, professeur, restaurant, douloureux, gouverneur, caoutchouc, commandant, chaleureux, impuissant, compliment, pharmacien, rafraîchir, transistor, langoureux, distinctif, sentiment, compagnie, président, découvrir, réfléchir, compagnon, directeur, différent, tradition, manuscrit, précédent, impatient, perroquet, mécontent, saucisson, processus, monarchie, savoureux, tournevis, refroidir, dégoûtant, chapiteau, affaiblir, carburant, chimpanzé, indiscret, cornichon, nettoyeur, attractif, crevaison, aussitôt, pantalon, écrivain, résultat, japonais, mercredi, interdit, modestie, orphelin, capuchon, archipel, indécent, vigilant, logiciel, thérapie

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Results of a paper-and-pencil study to test the impact of instructions (counting syllables vs. counting parts) on the segmentation of words with silent E words in adults Participants Four groups of volunteer participants were enrolled. Participants were adult native speakers of French. Forty-two of them had to judge the number of syllables of written words, 43 had to judge the number of parts of written words, 36 had to judge the number of syllables of spoken words, and 37 had to judge the number of parts of spoken words. Stimuli A set of 60 bisyllabic words was selected in Lexique (New et al., 2004) very similarly to what was done in Experiments 1–3. Half of the words included a silent E (e.g., javelot) and were matched to control words (e.g., fardeau) on word frequency, number of letters, phonemes, orthographic neighbourhood, and summed bigram frequency. As in Experiments 1–3, all the words in the silent E set entail obligatory schwa deletion. Sixty trisyllabic filler words (e.g., livraison, caporal) were added. Procedure The testing was conducted in several lecture halls of first year students. Each student who agreed to participate received a sheet Table 5 Proportion of expected responses according to the number of syllables of targets words and the group of participant.

Proportion of responses (%)

Proportion of responses (%)

Written modality – ‘‘syllables” instructions Written modality – ‘‘parts” instructions Spoken modality – ‘‘syllables” instructions Spoken modality – ‘‘parts” instructions

Response ‘2’ for bisyllabic words

Response ‘3’ for trisyllabic words

49

98

53

95

65

96

73

94

of paper with some information to be filled (e.g., age, gender, mother tongue), and the instructions clearly explained along with an example (For example, if in the word MATIN you think there are 2 parts, write ‘2’, if you think it as three parts, write ‘3’ and so on). This was followed by four lines to be filled for practice trials and by 120 lines for the experimental trials. In each lecture halls, words were displayed either in the spoken or in the written modality with the Psyscope software (Cohen, MacWhinney, Flatt, & Provost, 1993). One out of two participants received a sheet of paper with the instructions asking them to judge the number of syllables of the words, while the others had to judge the number of parts of the words. At each trial, the number of the trial was displayed during 2.5 s (so that they could fill the good line on the sheet, in case they missed a word), followed by the word during 2.5 s.

Analyses One participant was excluded (spoken modality, instructions ‘‘parts”) because she failed to respond to roughly 30% of the words. Overall, in the four groups, the participants performed adequately, assigning on average fewer parts to shorter words (see Table 5). The distribution of responses to bisyllabic words as a function of group are presented in Fig. 5. The number of parts/syllables assigned to words varied between 1 and 4, with most responses corresponding to 2 and 3 parts/syllables. In both modalities, the proportion of two-part responses was submitted to separate analyses of variance on the participant means (F1) and on the item means (F2) as a function of word type (silent E, control) and instructions (syllables, parts). In the written modality, the proportion of two-part responses for silent E words was lower than for control words, F1(1, 83) = 2344.83, p < .001, F2(1, 58) = 1817, p < .001. There was no significant interaction with the instructions, F1(1, 83) = 0.33, p = .57, F2 (1, 58) = 3.19, p = .08. In the spoken modality, the proportion of two-part responses for silent E words was lower than for control words, F1(1, 70) = 200.59, p < .001, F2(1, 58) = 38.18, p < .001. Here the interaction was significant, F1(1, 70) = 7.10, p = .01, F2(1, 58) = 44.59, p < .001, with the effect (fewer responses ‘‘2”) being stronger with the instructions ‘‘syllables” than ‘‘parts”.

Written modality (syllables)

Written modality (parts)

100

100

75

75

50

50

25

25

0

1 part 2 parts 3 parts 4 parts

0 Control

Silent E

Control

Spoken modality (syllables)

Spoken modality (parts)

100

100

75

75

50

50

25

25

0

Silent E

1 part 2 parts 3 parts 4 parts

0 Control

Silent E

Type of bisyllabic words

Control

Silent E

Type of bisyllabic words

Fig. 5. Proportion of responses 1, 2, 3, and 4 according to the type of bisyllabic words, the instructions and modality. Error bars represent standard errors.

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