Elisabeth Beyersmann
email: lisi.beyersmann@mq.edu.au

Petroula Mousikou

Ludivine Javourey-Drevet

Sascha Schroeder

Johannes C Ziegler

Jonathan Grainger

Morphological processing across modalities and languages

Keywords: morphological processing, cross-linguistic, visual lexical decision; auditory lexical decision

The present study examined cross-linguistic differences in morphological processing in the visual and auditory modality. French and German adults performed a visual and auditory lexical decision task that involved the same translation-equivalent items. The focus of the study was on nonwords, which were constructed in a way that the independent role of stems and suffixes in visual and auditory processing could be investigated. Results revealed a stem-by-modality and a suffix-by-modality interaction, indicating a more prominent role for morphology in the visual than in the auditory domain. Moreover, a significant language-by-stem interaction indicated more robust morphological processing in German than in French. The latter result supports the idea that morphological processing is influenced by the morphological productivity of a language.

How morphologically complex words are processed has been extensively investigated over the past few decades. However, few studies have investigated this issue across languages and modalities. The present study was designed to address two questions that have so far received little attention in the literature. The first question concerns if and how mechanisms of morphological processing differ depending on whether the input stimulus is a printed letter string or a speech signal. The second question asks how these mechanisms might differ across languages that vary in morphological productivity. Addressing these questions has the potential to advance theories of morphological processing by providing a broader modality-independent and language-universal perspective. The present study uses an innovative approach to answer each of these questions.

Morphological processing across modalities

In many Indo-European languages with concatenative morphology, sound-to-meaning mappings of morphologically complex words are typically less consistent than spelling-tomeaning mappings (e.g., [START_REF] Berg | Self-organization in the spelling of English suffixes: The emergence of culture out of anarchy[END_REF][START_REF] Berg | Morphological spellings in English[END_REF][START_REF] Rastle | The place of morphology in learning to read in English[END_REF][START_REF] Ulicheva | Skilled readers' sensitivity to meaningful regularities in English writing[END_REF]. For instance, in spoken English, the past tense is usually denoted by the allomorphs /əd/, /d/, or /t/ depending on surrounding context (e.g., busted, snored, kicked), whereas in written English, the corresponding phonemic sequences are always spelled ed (e.g., Carney, 1994;Desrochers, Manolitsis, Gaudreau, & Georgiou, 2017;[START_REF] Rastle | The place of morphology in learning to read in English[END_REF]. Similarly, the spelling of stems is preserved (e.g., magic, magical, magician), although this compromises the correspondence to their spoken forms [START_REF] Treiman | The development of spelling skill[END_REF]. The greater orthographic consistency of morphology in the written modality at the cost of spelling-to-sound consistency is also evident in German and French (e.g., Desrochers et al., 2017;[START_REF] Kuo | Morphological awareness and learning to read: A crosslinguistic perspective[END_REF][START_REF] Peereman | The contribution of morphology to the consistency of spelling-to-sound relations: A quatitative analysis based on French elementary school readers[END_REF]. In German, for example, the written form of morphologically related words (e.g., Sand-sandig, "sand-sandy") is preserved even when the spoken form varies (/zant/-/zandɪk/), where the 'd' in 'Sand' is pronounced /t/ due to devoicing (see also [START_REF] Landerl | Phonological and morphological consistency in the acquisition of vowel duration spelling in Dutch and German[END_REF]. Similarly in French, the spellings of morphologically complex words and their embedded stems are typically consistent (e.g. dent-dentier, "tooth-dentist"), whereas phonological forms tend to be more variable (e.g., the silent stem-final consonant 't' in 'dent' is pronounced when a suffix is added to the stem). The consistent spelling of morphemes enables the reader to identify morphological relationships between words, although the pronunciations of words belonging to the same morphological family may vary. Diachronic data on the evolution of suffix spellings from Old English indeed show that before the 16 th Century, adjectives were commonly spelled with the suffixes -ouse, -us, or -ows, but were then replaced with -ous over time [START_REF] Berg | Self-organization in the spelling of English suffixes: The emergence of culture out of anarchy[END_REF], thus making morphology highly visible in print (see [START_REF] Fuhrhop | Grammatik verstehen lernen -Grammatik sehen lernen[END_REF], for a similar phenomenon in German).

Of course, this does not necessarily imply that auditory and visual morphological representations in languages such as English, German and French are unrelated. There is plenty of evidence that spoken word knowledge influences reading processes (e.g., Beyersmann et al., in press;[START_REF] Johnston | Evidence for an automatic code in the processing of visually novel word forms[END_REF][START_REF] Mckague | The role of feedback from phonology to orthography in orthographic learning: An extension of item-based accounts[END_REF][START_REF] Wegener | Children reading spoken words: interactions between vocabulary and orthographic expectancy[END_REF]; and vice versa, it has been shown that reading has an impact on the processing of spoken language (for a review of the evidence, see [START_REF] Grainger | Cross-code consistency in a functional architecture for word recognition[END_REF]; see also [START_REF] Pollatsek | Oxford Handbook of Reading[END_REF]. Undoubtedly, there is an obvious transfer of written language knowledge to spoken language processing and vice versa (e.g., [START_REF] Frost | Speech and Spelling Interaction: The Interdependence of Visual and Auditory Word Recognition[END_REF]. However, given the greater consistency of morphology in print, it is possible that skilled readers acquire a specialized and highly automatized morphological parsing system, which is sensitive to the presence of morphological regularities during orthographic exposure. In spoken language on the other hand, morphological processing is unlikely to reach the same level of specialization, at least in languages where the link between morphologically complex spoken forms and their embedded morphemic constituents is often inconsistent, and as such, the identification of morphological structure is less reliable. Therefore, an important question that arises is whether morphological processing is more prominent and more automatized in written compared to spoken word recognition. We sought to answer this question in the present study.

Most studies to date have examined morphological processing either in written or in spoken language using a variety of experimental paradigms (for a recent review of the literature, see [START_REF] Beyersmann | Morphological processing without semantics: An ERP study with spoken words[END_REF]. However, rarely has a study directly compared morphological processing in the visual and auditory modality. Findings from the visual word recognition domain suggest that adults are experts at rapidly and automatically identifying morphological structures in print, independently of semantics (e.g., [START_REF] Amenta | Morphological processing as we know it: an analytical review of morphological effects in visual word identification[END_REF][START_REF] Beyersmann | Morpho-orthographic segmentation without semantics[END_REF][START_REF] Longtin | Morphological priming without morphological relationship[END_REF][START_REF] Rastle | Morphological decomposition based on the analysis of orthography[END_REF][START_REF] Rastle | The broth in my brother's brothel: Morphoorthographic segmentation in visual word recognition[END_REF]. In contrast, a review of the spoken word recognition literature [START_REF] Beyersmann | Morphological processing without semantics: An ERP study with spoken words[END_REF] indicates that morphological processing may be more reliant on semantics in this modality [START_REF] Marslen-Wilson | Morphology and Meaning in the English Mental Lexicon[END_REF][START_REF] Meunier | Morphological decomposition and semantic integration in word processing[END_REF][START_REF] Wurm | Auditory Processing of Prefixed English Words Is Both Continuous and Decompositional[END_REF][START_REF] Wurm | Auditory processing of polymorphemic pseudowords[END_REF][START_REF] Wurm | Conditional root uniqueness points: Psychological validity and perceptual consequences[END_REF]. In other words, on the basis of the available empirical evidence, formbased morphological processing is likely to be more prominent in visual than in auditory word identification.

To our knowledge, only one study so far has directly tested differences in morphological processing between the spoken and written modality [START_REF] Leinonen | Neurocognitive processing of auditorily and visually presented inflected words and pseudowords: evidence from a morphologically rich language[END_REF]. In a visual and auditory lexical decision task, in which event-related potentials (ERPs) were additionally recorded, [START_REF] Leinonen | Neurocognitive processing of auditorily and visually presented inflected words and pseudowords: evidence from a morphologically rich language[END_REF] sought to investigate the processing of inflected Finnish words (compared to monomorphemic words) and inflected nonwords consisting of a nonword stem and an inflectional suffix (compared to monomorphemic nonwords consisting of a nonword stem and a non-morphemic ending). The behavioral results from both types of tasks showed that participants responded more slowly to inflected words compared to monomorphemic words, but there was no difference between the two types of nonwords. This pattern was also reflected in the ERP analyses, where inflected words elicited a more negative N400 compared to monomorphemic words. The single word N400 component is generally thought to reflect word form processing difficulty (e.g., [START_REF] Perre | When beef primes reef more than leaf: Orthographic information affects phonological priming in spoken word recognition[END_REF][START_REF] Winsler | An electrophysiological megastudy of spoken word recognition[END_REF], with N400 amplitude increasing with an increased difficulty in identifying words and associating them with meaning (e.g., [START_REF] Grainger | Watching the word go by: On the time-course of component processes in visual word recognition[END_REF]. The greater N400 for inflected words compared to monomorphemic ones was obtained in both modalities, which the authors interpreted as processing costs associated with access and possible integration of the stem and suffix. [START_REF] Leinonen | Neurocognitive processing of auditorily and visually presented inflected words and pseudowords: evidence from a morphologically rich language[END_REF] also reported a significant N400 effect in the inflected nonwords relative to their monomorphemic nonword counterparts, which was significant in the visual but not in the auditory modality. Thus, the ERP results from this study provide some initial evidence that morphological structure may have more impact on visual than on auditory processing.

Morphological processing across languages

Given that Finnish is a morphologically productive language, it is possible that the effects observed by [START_REF] Leinonen | Neurocognitive processing of auditorily and visually presented inflected words and pseudowords: evidence from a morphologically rich language[END_REF] were due to the prominent role of morphology in Finnish.

This relates to the second question we addressed in this study, which is whether morphological processing in the visual and auditory modality may be modulated by the morphological productivity of a language. Morphological productivity refers to how specific morphological word-formation patterns may be used in the production of new forms [START_REF] Bauer | Morphological productivity[END_REF]. Morphemic units (including both affixes and stem morphemes) display large variability in morphological productivity [START_REF] Hay | Parsing and productivity[END_REF]. The more often a morpheme occurs in morphologically complex forms in the lexicon, the more productive this morpheme is thought to be. Critically, languages differ in this respect, and attempts to quantify morphological productivity across different alphabetic orthographies (for a review, see [START_REF] Borleffs | Measuring orthographic transparency and morphological-syllabic complexity in alphabetic orthographies: a Diependaele[END_REF] have not always yielded a consistent pattern of results. However, according to at least two of the methods used in the literature, namely, [START_REF] Juola | Measuring linguistic complexity: The morphological tier[END_REF][START_REF] Juola | Assessing linguistic complexity[END_REF], and the most recent and comprehensive Type-token ratio (TTR; [START_REF] Kettunen | Can Type-Token Ratio be Used to Show Morphological Complexity of Languages[END_REF], French is morphologically less complex than German. It has been suggested that the abundant presence of compound words in the German language (e.g., Creutz & Lagus, 2005;Creutz, Lagus, Lindén, & Virpioja, 2005;[START_REF] Fleischer | Wortbildung der deutschen Gegenwartssprache[END_REF][START_REF] Meyer | Compound comprehension in isolation and in context: The contribution of conceptual and discourse knowledge to the comprehension of German novel noun-noun compounds[END_REF]) may be the reason why according to the above-mentioned methods, German appears to be so morphologically complex [START_REF] Sadeniemi | Complexity of European Union Languages: A comparative approach[END_REF]. German compounds are mostly right-headed and concatenated (Großvater [engl. grandfather]), whereas French compounds are typically left-headed and nonconcatenated (chef de police [engl. chief of police]) or hyphenated (grand-père [engl. grandfather]) [START_REF] Nicoladis | Word family size and French-speaking children's segmentation of existing compounds[END_REF]. The latter type is less frequent than the former and not very productive [START_REF] Nicoladis | When is a preposition a linking element? Bilingual children's acquisition o French comound nouns[END_REF]. German also permits the compounding of multiple meaning conveying units (e.g. Datenschutzexpertentagungshotel [engl. Meeting hotel for data protection experts]), which are generally written without intervening spaces (e.g., [START_REF] Inhoff | Complex Compounds in German: Interword Spaces Facilitate Segmentation but Hinder Assignment of Meaning[END_REF]. Given these key linguistic differences between French and German, we hypothesized that morphological processing should be more robust in German than in French. Specifically, due to the rich compounding system that characterizes the German language, Germans should likely be more expert at rapidly extracting embedded stem morphemes from fully concatenated complex forms. As opposed to affixes, stems are free-standing morphemes that can be mapped onto existing representations in the mental lexicon and therefore do not require a specialized morphological chunking mechanism [START_REF] Grainger | Edge-aligned embedded word activation initiates morpho-orthographic segmentation[END_REF]. [START_REF] Grainger | Edge-aligned embedded word activation initiates morpho-orthographic segmentation[END_REF] therefore argue that the mechanism by which stems are recognized is distinct from the mechanism by which affixes are being identified. Given their high exposure to compound words, we reasoned that Germans might develop certain proficiency at mapping embedded stems onto existing lexical representations, which will likely be reflected in more robust stem-identification effects in German than in French.

Present study

To test differences in morphological processing between the visual and auditory modality in French and German we used an experimental paradigm that allowed us to tightly control for both item-and language-specific variables. We conducted an auditory and a visual lexical decision task using the same translation-equivalent items in both tasks. We focused on the processing of morphologically complex nonwords by manipulating orthogonally the stem and the suffix. In particular, four conditions were created: Stem + Suffix (e. ). The primary advantage of this 2x2 design was that it allowed to tease apart the separate roles of the stem and the suffix, as well as their interactions. The selection of nonwords provided greater control over psycholinguistic variables that are known to influence language processing (e.g., word frequency).

Previous studies

It is worth noting that a number of studies in this research domain have included complex nonwords in their investigations, but these have been typically restricted to the comparison between Non-Stem + Affix vs. Non-Stem + Non-Affix [START_REF] Lavric | Tracking hierarchical processing in morphological decomposition with brain potentials[END_REF][START_REF] Zweig | A visual M170 effect of morphological complexity[END_REF], Stem + Affix vs. Non-Stem + Affix [START_REF] Taft | Lexical storage and retrieval of prefixed words[END_REF], Non-Stem + Suffix vs. Non-Stem + Non-Suffix vs. Stem + Non-Suffix [START_REF] Vannest | Interplay between morphology and frequency in lexical access: the case of the base frequency effect[END_REF], or Stem + Suffix vs. Stem + Non-Suffix [START_REF] Beyersmann | Morphological processing without semantics: An ERP study with spoken words[END_REF]Dawson, Rastle, & Ricketts, 2018). What these prior studies concurrently show is that the presence of morphemes in nonwords makes the process of rejecting a nonword in lexical decision harder, a finding that has been typically referred to as the "morpheme interference effect" [START_REF] Taft | Lexical storage and retrieval of prefixed words[END_REF]. However, what these studies were less able to address are the combined effects of stem and affix, because of the absence of a full factorial design.

Hypotheses

In sum, the present study investigated how morphological processing might differ in the visual and auditory modality as a function of the morphological productivity of a language. We hypothesized that a suffix-effect would be evidenced by slower reaction times (RTs) and higher error rates in the Suffix compared to the Non-Suffix conditions, whereas a stem-effect would be evidenced by slower RTs and higher error rates in the Stem compared to the Non-Stem conditions. This is because the presence of a suffix and/or a stem in nonwords should make their rejection harder during lexical decision. The combined stem-and suffix-effects should further result in a significant Stem-by-Suffix interaction, because the stem-effect would be larger for suffixed than for non-suffixed nonwords. We also expected more robust stem-and suffix-effects in the visual compared to the auditory modality (i.e., evidenced by significant Stem-by-Modality and Suffix-by-Modality interactions), because morphological structure is more consistently represented in print than aurally. Moreover, on the assumption that the morphological productivity of a language influences the degree of morphological processing both visually and aurally, we hypothesized that morphological processing, and in particular embedded stem recognition, should be more robust in German than in French (i.e., evidenced by a robust Language-by-Stem interaction). On the assumption that morphological productivity in German is attributed to its rich compounding rather than its derivational system [START_REF] Sadeniemi | Complexity of European Union Languages: A comparative approach[END_REF], it was less clear whether a Language-by-Suffix interaction would also emerge. If anything, this should be weaker or smaller in size than the Language-by-Stem interaction. Finally, as a byproduct of our key hypotheses listed above, it was further predicted that the additive weight of the larger morphology effects in the visual modality, and the larger morphology effects in the German language, would result in an overall larger modality effect in German (evidenced by a significant Language-by-Modality interaction), as well as larger morphology effects in the visual modality in German (evidenced by a significant Language-by-Modality-by-Stem interaction, and possibly a significant Language-by-Modality-by-Suffix interaction).

Experiment Method

Participants. A total of 96 adults, 48 French (4 males, 5 right-handed, Mean Age = 19.0, SD = 1.7) and 48 German (11 males, 5 left-handed, Mean Age = 24.7, SD = 3.8) participated in the study for monetary compensation. Participants were native speakers of their respective language, had normal or corrected-to-normal vision, and reported no hearing, reading, or language difficulties. Five French participants were bilingual (French-Italian, French-Portuguese, or French-English) and one was trilingual (French-Malagasy-English). Two German participants were bilingual (German-English, German-Bulgarian). The study was approved by the ethics committees of Aix-Marseille Université and the Max Planck Institute for Human Development, for the French and German participants, respectively. Prior to participating in the study, participants provided written, informed consent. Each participant completed both the visual and the auditory lexical decision task, while the order of the tasks was counterbalanced across participants.

Materials.

Sixty morphologically simple words corresponding to translation-equivalent nouns (e.g., nuit, Nacht [engl. night]), which often happened to be cognates (e.g., film), were selected from each language. These 60 words served as stems and were combined with five noun-forming, translation-equivalent suffixes in the two languages to form morphologically structured and non-morphologically structured nonword targets (see Table 1 for details concerning the selected suffixes). The French and German suffixes were matched as clozely as possible on number of letters (M = 3.6, SD = 0.5 vs. M = 3.4, SD = 0.6; t(4)=0.54, p =.621), number of phonemes (M = 2.0, SD = 0.6 vs. M = 2.8, SD = 0.6; t(4)=1.37, p =.242), and logarithmic suffix frequency1 (M = 3.2, SD = 0.3 vs. M = 2.9, SD = 0.5; t(4)=2.43, p =.072), for French and German, respectively. nightel]). After a letter was replaced in these stems, the resulting non-stems (i.e., nonwords) were combined with the same suffixes, forming nonwords in the Non-Stem + Suffix condition (e.g., naiteur, Nechter [engl. naghter]), or the same letter sequences, forming nonwords in the Non-Stem + Non-Suffix condition (e.g., naiterge, Nechtatz [engl. naghtel]). In addition, sixty words that also corresponded to translation-equivalent nouns in the two languages were selected and included in the study for the purpose of the lexical decision task. Half of these words, which often happened to be cognates too, were suffixed, hence morphologically complex (e.g., boulanger, Bäcker [engl. baker]), while the remaining half were non-affixed (e.g., diamant, Diamant [engl. diamond]), hence morphologically simple. 2Word frequency and Orthographic Levenshtein distance (OLD20: [START_REF] Yarkoni | Moving beyond Coltheart's N: A new measure of orthographic similarity[END_REF], were extracted from Lexique [START_REF] New | Lexique 2: A new French lexical database[END_REF] for French, and SUBTLEX-DE (Brysbaert et al., 2011) for German, both of which use film subtitles to calculate word frequencies. 3 The OLD20 is given by the number of edits (insertions, deletions, and substitutions) required to transform one word into another, and is based on the average edit distance of the 20 nearest neighbors in the lexicon. The higher the OLD20 value of a word or a nonword, the sparser its orthographic neighborhood. All items are shown in the Appendix and their psycholinguistic properties are displayed in Tables 2 and3.

Both the French and the German auditory targets were produced with the OS X Speech Synthesizer. The naturalness of the synthesized files was checked by two independent native speakers in each language. Auditory files were edited to ensure that any silence at the beginning and end of each item was removed. The order of trial presentation within each list was randomized across participants. Six practice items consisting of both words and nonwords were presented to the participants prior to the experimental trials.

Participants were tested individually, seated approximately 60 cm in front of a laptop or a PC monitor in a quiet room. Stimulus presentation and reaction time latencies were controlled by DMDX software [START_REF] Forster | DMDX: A Windows display program with millisecond accuracy[END_REF]. In the visual lexical decision task, participants were told that words and nonwords would appear on the screen one at a time. Participants were then instructed to press "K" if the letter string was a word and "D" if the letter string was a nonword.

Items were presented in lowercase letters. However, the first letter of the German items was uppercase, because the first letter of noun forms in German is always written in uppercase. Thus, for consistency, all German items were presented in the same format. Stimuli appeared in white on a black background (20-point Arial font) and remained on the screen for 3000 ms or until participants responded, whichever happened first. In the auditory lexical decision task, participants wore headphones and were told that they would hear a word or a nonword one at a time. Participants had to press the same buttons as for the visual lexical decision task to indicate whether the item they heard was a word or a nonword. A black cross appeared on a white background while the item was presented aurally, and remained on the screen for 3000 ms or until participants responded, whichever happened first. Reaction times were recorded from stimulus onset. In both tasks, participants were asked to respond as quickly and as accurately as possible.

Analyses

Analyses were performed using (generalized) linear mixed-effects models [START_REF] Baayen | Mixed-effects modeling with crossed random effects for subjects and items[END_REF] as implemented in the lme4 package (Version 1.1-20; [START_REF] Bates | Fitting Linear Mixed-Effects Models Using lme4[END_REF] in the statistical software R (Version 3.5.1, 2018-07-02, "Feather Spray", RCoreTeam, 2018). RTs were log transformed to normalize residuals and were then analyzed using a linear mixed-effects (LME) model. For the error analysis, a generalized linear mixed-effects (GLME) model was created using logit transformation and a binomial link function. The significance of the fixed effects was determined with type III model comparisons using the Anova function in the car package [START_REF] Fox | An R companion to applied regression[END_REF]. Post hoc comparisons were carried out using cell means coding and single df contrasts with the glht function of the multcomp package [START_REF] Hothorn | Simultaneous inference in general parametric models[END_REF] using the normal distribution to evaluate significance.

The data from both languages and tasks were analyzed together. Given that nonwords were the focus of interest in the present study, we only report the nonword analyses. First we report the RT analyses and then the accuracy analyses. The results from the mixed-effects analyses are provided in Table 4 and the mean model RTs and error rates are displayed in Figures 1 and2.

Results

Reaction Times

Incorrect responses to nonwords (7.1% of the data) were first removed. Any latencies below 200 or above 2000 ms (1.3% of the data) were considered as extreme values and were also removed. Outliers were subsequently removed following the procedure outlined by [START_REF] Baayen | Analyzing reaction times[END_REF]. In particular, a base model, which included only participants and items as random intercepts, was fitted to the data and data points with residuals exceeding 2.5 SDs were removed (0.7% of the data). The LME model included the effect-coded fixed effects of Language (French vs. German), Stem (Stem vs. Non-Stem), Suffix (Suffix vs. Non-Suffix), and Modality (Auditory vs. Visual), as well as their interaction. Trial Order, OLD20, Letter Length, and Phoneme Length (all standardized) were included in the model as covariates. Random intercepts and random slopes for the effects of Stem and Suffix, and their interaction, were used for both subjects and items.

Stem and suffix effects

The

Modality effects

The main effect of Modality was significant. Nonwords in the auditory lexical decision task (M = 1038 ms, SE = 13) were responded to significantly slower (Δ = -273 ms, z = 78.100, p <.001) than nonwords in the visual lexical decision task (M = 765 ms, SE = 10). Furthermore, the interaction between Stem and Modality was significant. The stem effect in visual lexical decision (Δ = 70 ms, z = -12.150, p <.001) was larger than the stem effect in auditory lexical decision (Δ = 49 ms, z = -6.273, p <.001). Also, the interaction between Suffix and Modality was significant.

The suffix effect was significant in visual lexical decision (Δ = 54 ms, z = -9.390, p <.001), but not in auditory lexical decision (Δ = -12 ms, z = 1.575, p = .115). Accordingly, the triple Stem by Suffix by Modality interaction was significant. This was because the stem effect was much larger for suffixed nonwords than for non-suffixed nonwords in the visual lexical decision task (z = 6.035, p <.001), compared to the auditory lexical decision task (z = 2.188, p = 0.029).

Language effects

The main effect of Language was significant. French participants (M = 974 ms, SE = 18)

were significantly slower (Δ = -158 ms, z = 6.873, p <.001) than German participants (M = 815 ms, SE = 15). Critically for the hypotheses tested in the present study, the Language by Stem interaction was significant. The stem effect in German (Δ = 69 ms, z = 9.580, p <.001) was much larger than the stem effect in French (Δ = 52 ms, z = 5.925, p <.001). Even though the Language by Suffix interaction only approached significance, post-hoc contrasts revealed that the suffix effect in German (Δ = 34 ms, z = 4.801, p <.001) was larger than the suffix effect in French (Δ = 17 ms, z = 1.885, p =.060). In addition, the interaction between Language and Modality was significant. Differences between the visual and aural tasks in German (Δ = 284 ms, z = -63.580, p <.001) were much larger than differences between the two types of tasks in French (Δ = 258 ms, z = -47.100, p <.001). As per our predictions, the interaction between Language, Stem, and Modality were significant. Post-hoc contrasts showed that the stem effect was not modulated by type of task in French (z = 1.635, p = 0.102), but it was significantly bigger in visual than in auditory lexical decision in German (z = 6.428, p <.001).

Taken together, our results show that morphology plays an important role both visually and aurally. However, morphological influences seem to be more robust in the visual than in the 20 auditory domain. In addition, morphological processing seems to be more robust in German than in French. Also, compared to French, the observed morphological effects in German are much more prominent in the visual than in the auditory modality.

Accuracy

The error analyses were conducted in the same way as for RTs. The GLME model included the same fixed effects and interactions as the LME model, . OLD20, Letter Length, and

Phoneme Length (all standardized) were included in the model as covariates.

Stem and suffix effects

The main effect of Stem was significant. Nonwords with stems (M = 5.0, SE = 0.5) yielded more errors (Δ = 3.3, z = -7.608, p <.001) than nonwords without stems (M = 1.7, SE = 0.2). Also, the main effect of Suffix was significant. Nonwords with suffixes (M = 5.4, SE = 0.6) yielded more errors (Δ = 3.8, z = -7.844, p <.001) than nonwords without suffixes (M = 1.6, SE = 0.2).

Modality effects

The interaction between Stem and Modality was significant. Nonwords with stems yielded more errors in the visual lexical decision task (Δ = 4.3, z = 7.505, p <.001) than in the auditory lexical decision task (Δ = 2.4, z = 4.349, p <.001).

Language effects

The interaction between Language, Stem, and Modality was significant. Post-hoc contrasts showed that the stem effect was not modulated by type of task in French (z = -0.598, p = .550), but it was significantly bigger in visual than in auditory lexical decision in German (z = -3.247, p =.001). In addition, the interaction between Language, Stem, Suffix, and Modality was significant. This was because the stem effect for nonwords with and without suffixes was similar across modalities in French (z = -0.302, p = .763), but it was much bigger in the visual than in the auditory modality in German (z = 2.353, p = .019).

Taken together, the results from the analyses on nonword accuracy showed that morphological effects in German are more prominent in the visual than in the auditory modality.

Discussion

The present study is the first to investigate morphological processing in different modalities (visual vs. auditory) in a cross-linguistic fashion (French vs. German). To study the combined effect of morphemic stems and suffixes, we focused our investigations on four types of morphologically complex nonwords, namely nonwords consisting of a Stem + Suffix, a Stem + Non-Suffix, a Non-Stem + Suffix, and a Non-Stem + Non-Suffix. Our results revealed robust differences between modalities and languages. We summarize these below.

The first goal of our study was to test the hypothesis that morphological processing may be more prominent in the visual than in the aural modality, given that morphology is represented more consistently in written language (e.g., Desrochers et al., 2017;[START_REF] Landerl | Phonological and morphological consistency in the acquisition of vowel duration spelling in Dutch and German[END_REF][START_REF] Rastle | The place of morphology in learning to read in English[END_REF]. Our data support this hypothesis, showing that morphological structure has a greater impact on processing in the visual than in the auditory modality. This was evidenced by significant Stem-by-Modality and Suffix-by-Modality interactions (see Figures 1 and2). This is a novel finding, not only because the direct comparison between processing of derivational morphology in the two modalities has not been previously made, but also because our experimental design allowed us to clearly dissociate the role of the stem and the suffix in visual and auditory recognition processes. Our data show that the presence of a stem or a suffix made it more difficult to reject a nonword in a lexical decision task, and that this difficulty was greater in the visual than in the auditory domain. This suggests that in the visual modality, stems and suffixes were more rapidly identified and mapped onto existing morphemic representations than in the auditory modality. Therefore, our data provide support for the hypothesis that morphology plays a more prominent role in visual than in auditory word recognition, presumably because of the greater consistency of morphological units in printed form.

In addition, we investigated whether morphological processing is modulated by languagespecific differences in morphological productivity. On the assumption that German is more morphologically productive than French (e.g., [START_REF] Juola | Assessing linguistic complexity[END_REF][START_REF] Kettunen | Can Type-Token Ratio be Used to Show Morphological Complexity of Languages[END_REF][START_REF] Sadeniemi | Complexity of European Union Languages: A comparative approach[END_REF], we hypothesized that morphological processing effects would also be greater in German than in French. Our results revealed a significant Language-by-Stem interaction, while the Language-by-Suffix interaction approached significance, showing that the influence of morphologyand in particular stem processingwas more robust in German than in French.

This finding was further supported by a three-way interaction between Language, Stem, and Modality, which was significant both in terms of response latencies and accuracy (see Figures 1 and2). The significantly larger stem effect in German compared to French indicates that German speakers are more proficient in rapidly extracting embedded stems, and this seems to be particularly robust in the visual domain. Our data thus suggest that the lexical system benefits from repeated exposure to morphological regularities, as it is the case in morphologically productive languages like German. We speculate that the productivity of the compounding system, for which German stands out as being one of the most productive amongst Indo-European languages, might be the reason why stem extraction is effortless in this language. 4One question that arises from the present findings is whether the identification of stem morphemes and affixes is based on the same core processing mechanisms, or whether the two of morphemes have an entirely different status in the word recognition system. The first option is that the processing of stems and affixes is governed by the same morphological chunking mechanisms, but that the efficiency of the mechanism is determined by how frequently stems and suffixes are used within a specific language context. This is in line with theories suggesting that morphologically complex words (e.g., farmer) are initially "decomposed" and mapped onto specialized morphemic representations (e.g., the stem farm and the suffix -er), which are then in turn used to generate the combined meaning of the whole word (e.g., [START_REF] Baayen | War and peace: Morphemes and full forms in a noninteractive activation parallel dual-route model[END_REF][START_REF] Beyersmann | Parallel processing of whole-words and morphemes in visual word recognition[END_REF]Crepaldi, Rastle, Coltheart, & Nickels, 2010;Diependaele, Sandra, & Grainger, 2009;[START_REF] Taft | Morphological representation as a correlation between form and meaning[END_REF]. However, on the assumption that stems and affixes are handled by the same kind of decompositional mechanism and are therefore closely associated, it is more difficult to explain why the observed cross-linguistic differences in the stem effect were more robust than those in the suffix effect.

The alternative option is based on a more recent proposal by [START_REF] Grainger | Edge-aligned embedded word activation initiates morpho-orthographic segmentation[END_REF] who argued that stems and suffixes are processed in different ways. While affixes always occur in combination with a stem morpheme, stems themselves can occur as free-standing lexical units and therefore do not require setting up any specialized morphological representations (see also Beyersmann & Grainger, 2018). As such, stems can be activated simply by mapping embedded stems onto existing whole-word representations in the lexicon. This idea finds support in recent evidence from masked priming data in the lexical decision task, showing that embedded stems are rapidly activated independently of whether they are accompanied by a suffix or a nonmorphemic ending (e.g., [START_REF] Beyersmann | Language proficiency and morpho-orthographic segmentation[END_REF][START_REF] Beyersmann | Embedded Stem Priming Effects in Prefixed and Suffixed Pseudowords[END_REF]Beyersmann et al., 2018;[START_REF] Hasenäcker | Masked morphological priming in German-speaking adults and children: Evidence from response time distributions[END_REF][START_REF] Heathcote | Do 'blacheap' and 'subcheap' both prime 'cheap'? An investigation of morphemic status and position in early visual word processing[END_REF][START_REF] Morris | Effects of lexical status and morphological complexity in masked priming: An ERP study[END_REF][START_REF] Mousikou | Morphological processing in single-word and sentence reading[END_REF][START_REF] Taft | What cross-morphemic letter transposition in derived nonwords tells us about lexical processing[END_REF]. Suffixes on the other hand require a specialized chunking mechanism by which they are identified and removed from the rest input signal. The identification of an affix then sends in turn an activation boost to the embedded stem, which explains why masked priming studies with affixed and pseudo-affixed words (e.g., [START_REF] Longtin | Morphological priming without morphological relationship[END_REF][START_REF] Rastle | Morphological decomposition based on the analysis of orthography[END_REF][START_REF] Rastle | The broth in my brother's brothel: Morphoorthographic segmentation in visual word recognition[END_REF] typically show more priming to their embedded stems (e.g., farmer-farm and corner-corn) than non-affixed control words (e.g., cashew-cash). On the assumption that stems and affixes are handled by two entirely different mechanisms, this theoretical framework is in a better position to explain the presence of a significant Language by Stem interaction (i.e. a bigger stem effect in German than in French) in the absence of a significant Language by Suffix interaction. Stem-stem combinations form a central component of the German lexical system due to the productivity of the compounding system. Naturally, repeated exposure to compound words would then lead to the development of an efficient routine procedure to rapidly map embedded stems onto existing representations in the mental lexicon, while leaving the affix-chunking mechanism unaffected. Hence, Grainger and Beyersmann's ( 2017) theoretical framework provides an explanation for the present findings.

Finally, the results revealed an expected main effect of modality, showing that responses were overall slower in auditory than in visual lexical decision. While the visual system can perform a quick initial form-based analysis of the letter string, the seriality of the spoken input imposes a minimal time for word identification. A key follow-up of the current investigation would therefore be the examination of prefixed nonwords, to test if modality differences are replicable when the seriality of stem and affix is reversed. The main effect of language was also significant, showing that German participants responded overall faster than French participants, and so was the language-by-modality interaction, indicating greater language differences in the visual modality. French has less consistent print-to-sound and sound-to-print mappings than German [START_REF] Ellis | The effects of orthographic depth on learning to read alphabetic, syllabic, and logographic scripts[END_REF][START_REF] Seymour | Foundation literacy acquisition in European orthographies[END_REF]. Thus, differences in response latencies between the two samples could be due to the substantial number of silent letters in the French nonwords (compare number of letters to number of phonemes for French in Table 2). The presence of silent letters in the French nonwords would likely increase the uncertainty of printto-sound and sound-to-print mappings in this language, thus slowing down decision times in the French sample.

In sum, the present data provide a broader cross-modality and cross-linguistic perspective on the mechanisms involved in morphological processing. The greater impact of morphology within the written modality, which we hypothesize is likely due to the greater consistency of morphology in print, suggests that adults clearly benefit from morphological knowledge during reading. Moreover, the observed cross-linguistic differences in morphological processing demonstrate that language-specific characteristics can influence the cognitive mechanisms underlying visual and auditory word recognition.

  g., nuit + eur = nuiteur, Nacht + er = Nachter [engl. nighter]), Stem + Non-Suffix (e.g., nuit + erge = nuiterge, Nacht + atz = Nachtatz; where erge and atz are non-morphemic endings in French and German, respectively [engl. nightel]), Non-Stem + Suffix (e.g., nait + eur = naiteur, Necht + er = Nechter; where nait and Necht are nonwords [engl. naghter]), and Non-Stem + Non-Suffix (e.g., nait + erge = naiterge, Necht + atz = Nechtatz [engl. naghtel]

  main effect of Stem was significant. Nonwords with stems (M = 922 ms, SE = 12) were responded to significantly slower (Δ = -62 ms, z = 10.800, p <.001) than nonwords without stems (M = 861 ms, SE = 11). Also, the main effect of Suffix was significant. Nonwords with suffixes (M = 904 ms, SE = 12) were responded to significantly slower (Δ = -26 ms, z = 4.586, p <.001) than nonwords without suffixes (M = 878 ms, SE = 11). Moreover, the Stem by Suffix interaction was significant. The stem effect for suffixed nonwords (Δ = -89 ms, z = 10.890, p <.001) was substantially larger than the stem effect for non-suffixed nonwords (Δ = -35 ms, z = 4.781, p <.001).

Figure 1 .

 1 Figure 1. Lexical Decision Latencies (in Milliseconds) and Standard Errors for Nonwords in

Figure 2 .

 2 Figure 2. Accuracy (% Error) and Standard Errors for Nonwords in Visual and Auditory LDT.

Table 1 .

 1 Translation equivalent French and German suffixes and their meanings. Stems were either combined with suffixes, forming nonwords in the Stem + Suffix condition (e.g., nuiteur, Nachter [engl. nighter]), or a letter sequence that did not correspond to a suffix, forming nonwords in the Stem + Non-Suffix condition (e.g., nuiterge, Nachtatz [engl.

	German French	English* Examples (German; French)	Suffix meaning
	ung	ion	ion	Trennung; separation (Engl. separation)	(result of) an action or process
	bar	able	able	ersetzbar; remplaçable (Engl. replaceable)	able to be done; suitable; subject to
	keit	ment	ment	Dankbarkeit, remerciement (Engl. acknowledgement)	action or result of what is denoted by the stem
	er	eur	er	Arbeiter, travailleur (Engl. worker)	forms agent nouns from the stem
	haft	eux	ful	zweifelhaft; douteux (Engl. doubtful)	possessing the quality expressed by the stem
	*English translations are provided for reporting purposes only.

Table 2 .

 2 Psycholinguistic Properties of French and German Nonwords (SDs in Parentheses).

	Nonwords	Stem+Suffix Stem+Non-Suffix	Non-stem+Suffix Non-stem+Non-Suffix
			French
	OLD20	2.5 (0.6)	2.9 (0.5)	2.7 (0.6)	3.2 (0.6)
	N letters	8.1 (1.3)	8.2 (1.1)	8.1 (1.3)	8.1 (1.2)
	N phonemes 5.7 (1.3)	6.2 (1.1)	5.9 (1.3)	6.3 (1.2)
			German
	OLD20	2.8 (0.6)	2.7 (0.5)	3.0 (0.7)	2.9 (0.5)

Table 3 .

 3 Psycholinguistic Properties of French and German Suffixed Words, Non-Suffixed Words and Stems of Nonwords (SDs in Parentheses).Procedure. A total of three hundred items (60 words and 240 nonwords) in each language were used in the study. The nonword items belonged to four conditions: Stem + Suffix,

	Words	Suffixed Words	Non-Suffixed Words	Stems of Nonwords
			French
	OLD20	2.3 (0.5)	2.0 (0.5)	1.5 (0.4)
	N letters	8.1 (1.2)	6.7 (0.8)	4.6 (1.0)
	N phonemes 6.4 (1.4)	5.0 (0.9)	3.2 (1.0)
	Frequency	4.0 (0.6)	3.7 (0.6)	4.4 (0.9)
			German
	OLD20	2.3 (0.5)	2.3 (0.4)	1.4 (0.4)
	N letters	7.7 (1.2)	6.7 (0.8)	4.3 (1.0)
	N phonemes 6.3 (1.1)	6.2 (1.3)	4.0 (0.9)
	Frequency	4.1 (0.5)	3.8 (0.6)	4.7 (0.6)

non-suffixed). Hence, all conditions were represented in each list. An equal number of participants were assigned to each list. The word and nonword items were presented intermixed.

Table 4 .

 4 Summary of Linear Mixed-Effects Analyses for Nonword RTs and Accuracy.

	Variables	RTs		Accuracy
		χ 2	p	χ 2	p
	Fixed effects (df)
	Intercept (1)	287390.000 <.001	950.155	<.001
	Language (1)	47.243	<.001	1.688	=.194
	Stem (1)	116.610	<.001	79.790	<.001
	Suffix (1)	21.028	<.001	59.600	<.001
	Modality (1)	6099.800	<.001	0.635	=.426
	Stem:Suffix (1)	24.379	<.001	1.130	=.288
	Stem:Modality (1)	32.021	<.001	8.279	=.004
	Suffix:Modality (1)	111.290	<.001	0.811	=.368
	Language:Stem (1)	6.317	=.012	1.389	=.239
	Language:Suffix (1)	3.592	=.058	1.851	=.174
	Language:Modality (1)	112.770	<.001	0.041	=.840
	Language:Stem:Suffix (1)	2.243	=.134	0.168	=.682
	Language:Stem:Modality (1)	11.006	=.001	4.714	=.030
	Language:Suffix:Modality (1)	0.178	=.673	0.288	=.591
	Stem:Suffix:Modality (1)	12.184	<.001	2.676	=.102
	Language:Stem:Suffix:Modality	0.001	=.977	3.947	=.047
	(1)
	Order	155.580	<.001
	OLD20	26.390	<.001	40.827	<.001
	Letter Length	56.361	<.001	22.706	<.001
	Phoneme Length	36.216	<.001	2.141	=.143

Suffix frequencies were extracted from CELEX[START_REF] Baayen | The CELEX lexical database (CD-ROM)[END_REF] for German and Lexique(New, Pallier, Brysbaert, & Ferrand,

2004) for French. We note however that the suffix frequency measures for the two languages are not directly comparable, because the size of the corresponding corpora and the morphological segmentation methods that were used in each case differed.

Due to an oversight, three German non-suffixed words (Bescheid, Existenz, Frisur) were originally incorrectly chosen as suffixed. However, for the calculation of the psycholinguistic properties of the items and the analyses, these items were classified as non-suffixed.

It is worth noting that just like suffix frequencies, stem frequencies in the two languages cannot be directly compared, because the size of the corresponding corpora are substantially different.

It is worth noting that in a recent cross-linguistic study that investigated morphological effects on reading aloud as a function of the orthographic consistency and morphological complexity of a language(Mousikou et al., 2019), we observed that it is the orthographic consistency of a language, rather than its morphological complexity, that influences morphological processing in reading aloud. However, the consistency with which letters in a certain language map onto phonemes is critical for reading aloud, which could explain why this particular language characteristic influenced morphological processing in this task over and above morphological complexity.

Acknowledgements

This research was supported by grants from the French National Agency for Research (ANR) and the German Research Foundation (DFG), in particular the French-German ANR/DFG grant scheme in social sciences and humanities (ANR-15-FRAL-0003-01) and a DFG grant (SCHR-1268/2-1). The research also benefitted from support from grants ANR-16-CONV-0002, ANR-11-LABX-0036). EB was supported by a Discovery Early Career Researcher Award (DECRA) by the Australian Research Council (DE190100850), and JG by ERC grant 742141.

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