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.
In this study, we investigated the interaction between givenness and complexity on the choice of syntactic structure, via two experiments using speeded acceptability judgments. Experiment 1 showed that for the Danish dative alternation, given-new orders are only easier to process for double-object or NP constructions, whereas PP constructions are unaffected. This replicates previous findings for the English dative alternation. Experiment 2 revealed that when a long NP precedes a short NP-a suboptimal complexity relation-the effect of givenness is neutralized, whereas givenness remains influential when the complexity relation between the NPs in the sentence is optimal. This is consistent with the view that in online parsing, the actual syntactic structure-building process is primary, whereas any higher-order computations such as discourse linking are secondary. The relative complexity of the NPs in the double-object construction directly affects the structurebuilding process, whereas the decoding of the discourse structure is a later and less crucial phenomenon, resulting in neutralization of the givenness effect in cases in which the complexity relation is suboptimal.
Most research on cognates has focused on words presented in isolation that are easily defined as cognate between L1 and L2. In contrast, this study investigates what counts as cognate in authentic texts and how such cognates are read. Participants with L1 Danish read news articles in their highly proficient L2, English, while their eye-movements were monitored. The experiment shows a cognate advantage for morphologically simple words, but only when cognateness is defined relative to translation equivalents that are appropriate in the context. For morphologically complex words, a cognate disadvantage is observed which may be due to problems of integrating cognate with non-cognate morphemes. The results show that fast non-selective access to the bilingual lexicon is conditioned by the communicative context. Importantly, a range of variables are statistically controlled in the regression analyses, including word predictability indexed by the conditional probability of each word.
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