232App<strong>en</strong>dice Ito an orthographic lexicon of 2494 words (for a detailed <strong>des</strong>cription of the cleaning proce<strong>du</strong>re applied on thisdatabase in order to extract the selected lexicon, see the app<strong>en</strong>dix).This multil<strong>en</strong>gth lexicon raises the issue of how to code letter-in-word position and the relation betwe<strong>en</strong>word units of differ<strong>en</strong>t l<strong>en</strong>gths. Some rec<strong>en</strong>t empirical studies suggest that the cognitive system uses relativerather than absolute position coding (Grainger & Jacobs, 1993 ; Peressotti & Grainger, 1995 ; see alsoGrainger & Jacobs, pres<strong>en</strong>t volume). Thus, letters in a word are not supposed to be repres<strong>en</strong>ted in terms oftheir absolute position in the word (i.e., U at the third position in BLUE), but in terms of their relative position,which is calculated from the word boundaries (e.g., U is one position before the final letter and L isone position after the initial letter in BLUE, i.e. U=final -1 and L=initial +1, respectively). This codingscheme allows us to establish more plausible similarity relations betwe<strong>en</strong> words of differ<strong>en</strong>t l<strong>en</strong>gths than theoriginal position coding scheme of the IAM 7 . As an example, the stimulus WORD is <strong>en</strong>coded as : W ininitial position, O in initial +1, D in final position, and R in final -1. This coding scheme was applied tothe orthographic lexicon and for coding the input stimuli pres<strong>en</strong>ted to the model. Table 1 gives a g<strong>en</strong>eral<strong>des</strong>cription of our coding scheme for 3 to 5 letter words.OrthographicLexiconPhonologicLexiconLetterLevelPhonologicalUnit LevelVisual StimulusAuditory StimulusFigure 4 : Grainger and Ferrand's model (1994)WHOLE WORD PHONOLOGICAL LEXICON. In MROM-P we assume that each orthographic repres<strong>en</strong>tationof a word has a corresponding whole-word phonological repres<strong>en</strong>tation. The phonological lexicon containingthese repres<strong>en</strong>tations is smaller than the orthographic one because of homophones that have distinctorthographic <strong>en</strong>tries but share the same phonological code. This led to 2323 whole word phonological repres<strong>en</strong>tationsin contrast to the 2494 orthographic word units. Connections were established betwe<strong>en</strong> eachwhole-word orthographic unit and its corresponding whole-word phonologic unit, and specific values of restinglevel activation (i.e., coding frequ<strong>en</strong>cy of occurr<strong>en</strong>ce) were giv<strong>en</strong> to each unit using the CELEX frequ<strong>en</strong>cycount (see app<strong>en</strong>dix for a <strong>des</strong>cription of the proce<strong>du</strong>re).Table 1 : Relative position coding scheme for 3 to 5 letter wordsWord initial init.+1 init.+2 final-1 finall<strong>en</strong>gth5 L1 L2 L3 L4 L54 L1 L2 * L3 L43 L1 L2 * * L3PHONOLOGICAL UNITS. We assume that i) the cognitive system of a reader possesses some elem<strong>en</strong>taryphonological repres<strong>en</strong>tations or coding units ; ii) these basic phonological units, or phonemes, are grouped7 The evaluation of the plausibility of this coding scheme requires further investigation and, probably, further refinem<strong>en</strong>ts.The use of a more structured coding scheme, intro<strong>du</strong>cing a grapheme level composed of functional pronunciationunits as proposed by Berndt, D'Autrechy and Reggia (1994 ; Berndt, Reggia & Mitchum, 1987 ; Reggia,Marsland & Berndt, 1988) is a possible candidate for such refinem<strong>en</strong>ts. However, more constraining results ar<strong>en</strong>eeded to specify the nature and the boundaries of such units.
App<strong>en</strong>dice I 233according to a consonant, vowel, consonant (CVC) or, more precisely, an onset, nucleus, coda (ONC)scheme. This scheme is both motivated by curr<strong>en</strong>t linguistic theory (e.g., Wiese, 1996), and by empiricaldata (Dell, 1988). We chose this subsyllabic organization as a pragmatic, parsimonious compromise. Higherinfralexical phonological structures, like onset-rime units, for example, are less flexible and less g<strong>en</strong>eral.Lower structures, like ungrouped phoneme strings, for example, complicate the connectivity betwe<strong>en</strong> letterand phoneme units.The phonemic repres<strong>en</strong>tation level thus contains onset, nucleus and coda positions. These units can co<strong>des</strong>ingle phonemes or phoneme clusters. Furthermore, a "sil<strong>en</strong>t phoneme" is added at the onset and coda positionsin order to repres<strong>en</strong>t monosyllabic words that have no pronounced consonant at their beginning or <strong>en</strong>d.As an example, consider the stimulus GOOD. This is phonologically coded as /gUd/ and decomposed as :Onset = /g/ ; Nucleus = /U/ ; Coda = /d/. Similarly, BLUE (/blu/) is decomposed as : Onset = /bl/ ; Nucleus= /u/ ; Coda = /*/ (the star repres<strong>en</strong>ting the sil<strong>en</strong>t phoneme in the coda position). Table 2 shows thethree sets of phonological units of the MROM-P : They include all possible phonemes or combinations ofphonemes contained in the phonological lexicon of the model at each position.Table 2 : Description of the three sets of phonological unitsONSET51 unitsNUCLEUS34 unitsCODA78 units*, b, bl, br, d, D, dr, dw, f, fl, fr, g, gl,gr, h, J, k, kl, kr, kw, l, m, n, p,pl, pr,r, s, S, sk, skr,skw, sl, sm, sn, sp, spl,spr, Sr, st, str, sw, t, T, Tr, tr, tw, v, w,z, _1, 2, 3, 4, 5, 6, 7, 8, 9, #, $, @, E, i, I,j#, j$, j1, j3, j5, j7, j8, j9, jE, ji, jQ, ju,jV, j{, Q, u, U, V, {*, b, d, D, dst, dT, Dz, dz, f, fT, ft, g, gz,h, J, k, ks, ksT, kst, m, md, mf, mp, mps,mt, mz, kt, l, lb, ld, lf, lk, lm, ln, lp, lS,ls, lt, lT, lv, lz, l_,n, N, nd, ndz, nJ, Nk,Nks, nS, ns, nt, nT, nts, nz, nZ, Nz, n_,p, ps, pt, pT, R, s, S, sk, sCONNECTIONS BETWEEN LETTERS AND PHONOLOGICAL UNITS. Figure 5 illustrates our connectionscheme for linking orthographic and phonological units, a t<strong>en</strong>tative solution to the problem of discoveringan optimal grapheme-to-phoneme correspond<strong>en</strong>ce (GPC) scheme for IA-type models. In order to beconsist<strong>en</strong>t with the spreading activation (system) principle of IA models, we carried out an exhaustive analysisof the pres<strong>en</strong>t lexicon, recording all existing links betwe<strong>en</strong> each letter/grapheme -at each relative position-and each phonological unit -at the ONC positions. The results were stored in large matrices that codethe GPCs, such as the fact that B in initial position (like in BLUE) is connected to the phonological unit/bl/ at the onset position. Similarly, for the same word, L at the initial +1 position is connected to /bl/ inonset, U at the final-1 is connected to /u/ in nucleus, and so on. Thus, respecting the spreading activationmechanism of the model, wh<strong>en</strong> a letter like B is activated in initial position, it will s<strong>en</strong>d excitation to allcorresponding phoneme units in onset position, i.e., /b/, /bl/ and /bR/.Figure 5 : Connectivity betwe<strong>en</strong> the letter and phonological unit levels
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UNIVERSITÉ DE PROVENCE, AIX-MARSEI
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Ce travail clôt un cycle de format
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CHAPITRE 7 : LE FUM . . . . . . . .
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8IntroductionPour cela, notre domai
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10Introduction• au niveau lexical
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12Introduction• sa forme visuelle
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14IntroductionAprès avoir posé le
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16Méthodologiespulations sur les i
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18Méthodologies2.1. Protocoles exp
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20Méthodologiessi le stimulus se t
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22MéthodologiesCertaines études t
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24Méthodologiestes, on obtient des
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26Méthodologies1996 ; Peter & Turv
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28Méthodologiesles performances da
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30Méthodologies6 %8%10%15%30%50%80
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32MéthodologiesMatériel expérime
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34Méthodologiesentraîne le masqua
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36MéthodologiesLe même résultat
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38Méthodologies120100Situation Sta
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Chapitre 3Orthographe et phonologie
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42Orthographe et Phonologie3.1. Var
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44Orthographe et PhonologieLa Figur
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46Orthographe et PhonologieJacobs,
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48Orthographe et Phonologiedans la
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50Orthographe et PhonologieDans l
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52Orthographe et Phonologieteurs du
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54Orthographe et PhonologieGoldstei
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56Orthographe et Phonologietion est
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58Orthographe et Phonologierand, 19
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60Orthographe et Phonologieplus ad
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62Orthographe et Phonologie3.2.3.1.
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64Orthographe et PhonologiePlus ré
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66Orthographe et PhonologieUne autr
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68Orthographe et Phonologiedeux var
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Chapitre 4Modèles de la perception
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72Modèles de la perception visuell
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74Modèles de la perception visuell
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76Modèles de la perception visuell
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78Modèles de la perception visuell
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80Modèles de la perception visuell
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82Modèles de la perception visuell
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84Modèles de la perception visuell
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86Modèles de la perception visuell
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88Modèles de la perception visuell
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90Modèles de la perception visuell
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92Modèles de la perception visuell
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94Modèles de la perception visuell
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96Modèles de la perception visuell
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98MROM-pspécifier leur lien avec l
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100MROM-pphonèmes reliés par un r
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102MROM-pLorsque le modèle génèr
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104MROM-pque ce système artificiel
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106Unités de la lecturelinguistiqu
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108Unités de la lecture22606TR (ms
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110Unités de la lecturemes. Aussi
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112Unités de la lecturephonologiqu
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114Unités de la lectureelle-même
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116Unités de la lecture6.3. Expér
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118Unités de la lectureRead est qu
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120Unités de la lectureces modèle
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122Unités de la lecturechapitre su
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124FUMmultiples existant au sein de
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126FUMpar Berndt, Lynne D'Autrechy
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128FUMcessus de compétition et du
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130FUMgène et suit les principes c
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132FUMPseudohomophonesContrôles Or
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134FUM61023TR (ms) Seidenberg et al
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136FUMportementaux et les résultat
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138FUMà une entité extérieure au
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Chapitre 8Des prédictionsau niveau
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142Des prédictions au niveau des m
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144Des prédictions au niveau des m
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146Des prédictions au niveau des m
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148Des prédictions au niveau des m
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150Des prédictions au niveau des m
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152Des prédictions au niveau des m
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154Des prédictions au niveau des m
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156Des prédictions au niveau des m
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158Des prédictions au niveau des m
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160Des prédictions au niveau des m
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162Des prédictions au niveau des m
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164Des prédictions au niveau des m
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166Les mots polysyllabiquesmots mon
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168Les mots polysyllabiquesTableau
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170Les mots polysyllabiques9.2. Exp
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172Les mots polysyllabiques19001890
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174Les mots polysyllabiquesnexe XI
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176Les mots polysyllabiques9.4. Dis
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178ConclusionConclusion« La grande
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180Conclusionplutôt un système o
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- Page 184 and 185: 184BibliographieAderman, D., & Smit
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- Page 190 and 191: 190BibliographieGrainger, J., & Jac
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- Page 196 and 197: 196BibliographiePerea, M., & Pollat
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- Page 200 and 201: 200BibliographieTreiman, R., & Zuko
- Page 202 and 203: 202AnnexesAnnexes
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- Page 224 and 225: 224Appendice IMROM-P : An interacti
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- Page 228 and 229: 228Appendice Isummed frequency of f
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- Page 240 and 241: 240Appendice Iteractive processes o
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- Page 248 and 249: 248Appendice IAPPENDIXA1. Cleaning
- Page 250 and 251: 250Appendice IIA phoneme effect in
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