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The Case for a Sixth-Century Date of Composition

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Orthography to Phonology and Meaning: Comparisons Across and within Writing Systems | SpringerLink

Add to Cart. Have an Access Token? Enter your access token to activate and access content online. Please login and go to your personal user account to enter your access token. Have Institutional Access? Forgot your password? PDF Preview. The final step concerns the actual overt production of the printed word, the conversion of the orthographic or phonological representation into a phonetic code that activates the corresponding articulatory-motor program Browman and Goldstein, The goals of this review are: 1 to give insight into the time course of sub-lexical activation of orthography and phonology during reading aloud, 2 identify the locus of GPC, and 3 to propose how ERP results can inform computational models.

This topic has mostly been investigated with the lexical decision task LDT combined with the masked priming paradigm e. In masked priming, a visible target stimulus is preceded by the brief presentation of a prime stimulus to avoid strategic processing Forster, It is assumed that the sub-lexical segments of the masked prime are activated. When the target is presented and segments match, they are pre-activated and brain activity reaches a specified threshold faster Horemans and Schiller, However, LDT i. Therefore, it cannot be ascertained that sub-lexical GPC is captured.

When reading aloud is combined with masked priming the lexical effects are minimized. This mini-review focuses mainly on the latter research to capture sub-lexical GPC. It also focuses on electrophysiological measures to demonstrate the online time course of the GPC process before the endpoint of processing captured by behavioral data. Below, the computational models that simulate reading aloud will be described.

Phonemic orthography

Next, behavioral and event-related potentials ERPs studies revealing the underlying processes of reading aloud are discussed. Lastly, we discuss how well the models account for the behavioral and ERP findings in the literature. Models of reading can be distinguished based on the locus of the GPC process: early or late.

However, the early models modulate GPC rules in slightly different manners. For instance, according to the dual-route cascaded DRC model, in the lexical route, the phonology of a written word is retrieved as a whole parallel from the mental lexicon. In the non-lexical route, graphemes are transferred one by one serial into corresponding sound codes i.

From beginning-to-end of a word 1 , a rule is found for translating each letter into a phoneme e. Non-word reading can only be simulated by the non-lexical route because non-words do not have a lexical entry. Irregular words e. This causes competition between the routes, which slows down processing for irregular compared to regular words that have matching pronunciations for both routes see Figure 1 ; Coltheart et al.

What makes Icelandic "difficult" part 1: orthography and phonology

Evidence for serial processes comes from the beginning-to-end nature of the regularity effect, which demonstrates longer naming latencies for irregular words that have exceptional spelling early in the word e. Additional evidence comes from position dependency of the masked onset priming effect MOPE for onset-related but not offset-related prime-target pairs Forster and Davis, ; Kinoshita, ; Schiller, Schematic representations of computational models of reading aloud and speech production.

However, the non-lexical route is not rule based like the DRC model, but instead a simple two-layer network is employed. In this network the input layer represents the written word and the output layer represents the phonological representation belonging to the written word.

The network is trained on grapheme-phoneme correspondences, through a graphemic buffer, which means not only single letters but also multi-letter graphemes are represented e. The correct pronunciation is chosen in the phonological output buffer where the pronunciations of both routes come together i. The triangle model suggests orthography can be linked to phonology directly or mediated by semantics.

After the conversion of each word, the phonological output is compared to the phonological target word. Based on error for the output units, weights are updated to reduce the error. Models assuming an early locus of GPC suggest that a MOPE will only be present for low-frequency words and the effect will disappear when applying a lexical decision or conditional naming task i. However, this idea is not unchallenged; the speech-planning account has suggested a later locus of GPC, namely during the segment-to-frame association part of speech-planning Kinoshita, ; Kinoshita and Woollams, The MOPE is explained by a conflict from mismatching onset phonemes between prime and target holding up the segment-to-frame association process.

Other behavioral data, like the regularity effect, can also be explained by a hold up in the segment-to-frame association process Kinoshita, ; Kinoshita and Woollams, The models described above only address reading in one language. However, next to within-language priming, cross-language phonological priming reflects fast and automatic activation of both the first L1 and second language L2 GPC rules Dijkstra and van Heuven, The bilingual interactive activation BIA model Dijkstra and van Heuven, can explain L2—L1 cross-language priming effects because it assumes a single lexicon in which words from the different languages a bilingual speaks are simultaneously activated and interconnected i.

This is necessary because when bilinguals speak in one language, they must inhibit words from the non-target language to avoid interference.

follow site Current research supports the notion that at the lexical level, our languages are represented together i. However, is it only the lexical level where all languages are represented collectively or does it extend to the sub-lexical orthographic and phonological level? Models of reading suggest different loci of GPC: sub-lexical or during speech preparation. Facilitation for shared onset segments i. However, models assuming an early locus of GPC can explain the absence of a MOPE during LDT by means of an overall slowdown during the lexical decision process which dissolves any earlier facilitation effects.

Mini Review ARTICLE

In a similar manner, opaque Persian words i. The conflict between the incorrect pronunciation i. For transparent Persian words i. The speech-planning account explains these effects by a holdup during the segment-to-frame-association of speech-planning. For example, conditional naming i. The time criterion is set at a point in time that is appropriate for the type of words to be named correctly.

A later time criterion could also be adopted for irregular words. The later time criterion for irregular words could dissolve the effect of matching onset segments Kinoshita, ; Kinoshita and Woollams, Thus, these behavioral results cannot differentiate between the different accounts on the locus of the MOPE. Furthermore, behavioral results suggest that the MOPE, reflecting GPC, is phonological in nature; words that match on orthography but not phonology; e.


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However, response latencies are faster when phonology, rather than orthography, is matched e. The above literature demonstrating segmental priming MOPE employed alphabetic languages. Syllabic languages e. This difference may be due to the writing system i. Above, we have interpreted the findings in light of L1 research. For example, an L2 English prime that was phonologically related to the onset of an L1 Dutch target e.

These results suggest that both L1 and L2 phonology become rapidly activated from a masked prime while performing a task in the L1. In addition, under certain circumstances Mandarin—English bilinguals reveal segmental, instead of only syllabic, priming during Mandarin reading due to their knowledge of an alphabetic language Verdonschot et al.

However, that LDT promotes lexical processing. In addition, large prime-target overlap has often been used e. Therefore, studies using reading aloud and only segmental onset overlap provide stronger evidence for the time course of sub-lexical GPC, presenting itself as a negative ERP component between 80 ms and up to ms after target presentation Timmer and Schiller, ; Timmer et al. The peak occurred around ms during reading instead of ms during LDT. The reading aloud literature is in line, though slightly earlier, with a meta-analysis of word naming, proposing that the GPC process occurs approximately — ms after target presentation and not a late locus of GPC during speech preparation, as proposed by the speech-planning account Kinoshita, ; Kinoshita and Woollams, , within the — ms time window Indefrey and Levelt, ; Indefrey, Even stronger support for the early locus of GPC comes from the presence of phonological priming for both transparent and opaque Persian words in the 80— ms time window, though only transparent words showed a MOPE behaviorally.

During the — ms time window, phonological activation is only found for transparent Persian words Timmer et al. When the two routes come together, in the output buffer, the multiple pronunciation options for Persian opaque words slow down processing and eliminate the MOPE for opaque words in both the ERPs and the behavioral results. Just like opaque words Timmer et al. Based on the behavioral absence of a MOPE for opaque words but its presence in the early ERPs we would also expect early ERP effects for irregular words and unpronounceable non-words in possible future endeavors.

Averaged stimulus-locked event-related potential ERP waveforms during a masked priming paradigm demonstrate the online time course of grapheme-to-phoneme-conversion GPC during reading aloud. Transparent words i. For both word types, more negative amplitudes for phoneme-mismatch O-P-; e. This supports an early locus of GPC for both word types. During the — ms time window, this effect is only continued for the transparent words. This later time window might reflect processing in the output buffer. The multiple pronunciation options for Persian opaque words slow down processing and eliminate the masked onset priming effect MOPE for opaque words in both the ERPs and the behavioral results.

To conclude, ERPs demonstrate that in spite of the discrepancy in behavioral measures all word types have an early GPC.