Morphological decomposition based on the analysis of orthography

Rastle, Kathleen; Davis, Matthew H.

doi:10.1080/01690960802069730

Cited by 385 publications

(487 citation statements)

References 86 publications

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“…Furthermore, of those words that are not compounds or derived words, roughly a third carries an inflectional ending. The full-form approach of Shortlist B to morphological processing sets this model apart from theories assuming obligatory decomposition (see, e.g., Rastle and Davis (2008), for visual comprehension and Marslen-Wilson, Tyler, Waksler, and Older (1994), for auditory comprehension).…”

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Probability and surprisal in auditory comprehension of morphologically complex words

Balling

Baayen

2012

Cognition

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Two auditory lexical decision experiments document for morphologically complex words two points at which the probability of a target word given the evidence shifts dramatically. The first point is reached when morphologically unrelated competitors are no longer compatible with the evidence. Adapting terminology from Marslen-Wilson (1984), we refer to this as the word's initial uniqueness point (UP1). The second point is the complex uniqueness point (CUP) introduced by Balling and Baayen (2008), at which morphologically related competitors become incompatible with the input. Later initial as well as complex uniqueness points predict longer response latencies. We argue that the effects of these uniqueness points arise due to the large surprisal (Levy, 2008) carried by the phonemes at these uniqueness points, and provide independent evidence that how cumulative surprisal builds up in the course of the word co-determines response latencies. The presence of effects of surprisal, both at the initial uniqueness point of complex words, and cumulatively throughout the word, challenges the Shortlist B model of Norris and McQueen (2008), and suggests that a Bayesian approach to auditory comprehension requires complementation from information theory in order to do justice to the cognitive cost of updating probability distributions over lexical candidates.Keywords: spoken word recognition; Shortlist B; morphological processing; uniqueness points; neighbourhood measures; (cumulative) surprisal; Kullback-Leibler divergence; morphological family size. The Shortlist B model proposed by Norris and McQueen (2008) is the most comprehensive computational theory of auditory comprehension available to date. The model computes that sequence of words that is most likely to represent the lexical parse of the utterance heard, given the input, a stream of phonemes coming in over time. For instance, given the Dutch sequence of spoken words kar personen, the final state of the model is one in which kar ('cart') and personen ('persons') have probability 1, whereas competitors such as karper ('carp') and persoon ('persons') have probability 0.

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confidence: 99%

Probability and surprisal in auditory comprehension of morphologically complex words

Balling

Baayen

2012

Cognition

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“…With this in mind, we can conclude that our results, together with previous studies (for example Baayen et al, 2011;Milin et al, 2017), present a challenge for the obligatory segmentation stance in lexical processing and reading (for the most elaborate exposition of the segmentation approach consult Rastle, Davis, & New, 2004;Rastle & Davis, 2008). Instead of the default assumption that a word is segmented into its constituents (morphemes), which are recombined at later, consolidatory stages, the discrimination learning framework reveals a different kind of dynamics, where cue-outcome connections evolve gradually during learning, and neither cues nor outcomes are predetermined and static.…”

Section: Discussionmentioning

confidence: 53%

A learning perspective on individual differences in skilled reading: Exploring and exploiting orthographic and semantic discrimination cues.

Milin

Divjak

Baayen

2017

Journal of Experimental Psychology: Learning, Memory, and Cogni

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The goal of the present study is to understand the role orthographic and semantic information play in the behaviour of skilled readers. Reading latencies from a self-paced sentence reading experiment in which Russian near-synonymous verbs were manipulated appear well-predicted by a combination of bottom-up sub-lexical letter triplets (trigraphs) and top-down semantic generalizations, modelled using the Naive Discrimination Learner. The results reveal a complex interplay of bottom-up and top-down support from orthography and semantics to the target verbs, whereby activations from orthography only are modulated by individual differences. Using performance on a serial reaction time task for a novel operationalization of the mental speed hypothesis, we explain the observed individual differences in reading behaviour in terms of the exploration/exploitation hypothesis from Reinforcement Learning, where initially slower and more variable behaviour leads to better performance overall.

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“…The author of this research also observed that it was decided by the nature of the morphological decomposition. As an automatic processing mechanism for the derived words, the morphological decomposition was also activated when the brain perceived the morphological structures (Rastle & Davis 2008). Some researches found that this decomposition even occurred in the processing of the simple words (e.g.…”

Section: Theory and Practice In Language Studiesmentioning

confidence: 99%

“…On the other hand, a great number of researches on L1 have found that morphological decomposition was a processing mechanism for the complicated words that occurred automatically. This mechanism was activated at the early automatic stage of word identification and would occur even if the participants were unconscious of it (Rastle & Davis 2008), while the priming effect caused by morphological similarity or semantic relations would occur only at the conscious processing stage and it was hard for it to happen in the masked priming experiment when the priming words were presented in a very short period of time (Rastle et al 2004). In this research the visual test of the materials used after the experiment indicated that the participants did not perceive the existence of the priming words, and therefore there would be no morphological or meaningful priming.…”

Section: Theory and Practice In Language Studiesmentioning

confidence: 99%

“…The time for the presentation of the priming words was short (within 80ms), and there were a series of masked symbols (e.g.#) before the presentation, which ensured the fact that the participants processed the words unconsciously and avoided any impact of intentional processing strategies and effectively revealed the characteristics of automatic processing at the early stage of the priming words presentation. A great number of observations of L1 learners which employed this mode found out that affected by the inner structures of the words, there was morphological decomposition in the processing of complicated words and this decomposition occurred at the early stage of the word processing, proved to be an automatic processing mechanism for complex words and not affected by the factors such as word familiarity (Rastle & Davis 2008;McCormick et al 2009). …”

Section: Introductionmentioning

confidence: 99%

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Morphological Decomposition in Second Language Word Processing

Cao¹

2016

TPLS

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Abstract-This paper made a masked priming experiment to examine the Chinese learners' online processing of English derivatives or derived words so as to find out the effect of morphological structures on second language (L2) word processing. 39 Chinese freshmen of non-English majors participated in the experiment. Results indicated that derivatives had significant priming effect on the identification of their stems and that this kind of priming effect was not affected by the brain's familiarity with it, which meant that like L1, L2 derivative processing was also affected by the morphological structures and that morphological decomposition did exist. This conclusion supports the view of Diependaele et al. that the characteristics of the target words determined their processing mechanism. In addition, the main factors that affect the complicated processing mechanism prove to be the features which are composed of the morphemes instead of the features of the whole words.

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Morphological decomposition based on the analysis of orthography

Cited by 385 publications

References 86 publications

Probability and surprisal in auditory comprehension of morphologically complex words

Probability and surprisal in auditory comprehension of morphologically complex words

A learning perspective on individual differences in skilled reading: Exploring and exploiting orthographic and semantic discrimination cues.

Morphological Decomposition in Second Language Word Processing

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