Biomedical subjects

Patrick Sturt

Publications and source records attributed to Patrick Sturt.

7 recordsLinked to original sources

PubMed2006

Semantic re-interpretation and garden path recovery.

Participant's eye-movements were recorded while they read locally ambiguous sentences. Evidence for processing difficulty was found when the interpretation of the initially preferred misanalysis clashed with that of the globally correct analysis, demonstrating the persistence of the earlier interpretation. Processing difficulty associated with the syntactic reanalysis was largely localised to the disambiguating region, with difficulty due to semantic persistence occurring later. The results show that semantic persistence is not limited to extreme cases of parse failure, and can occur even when reanalysis is relatively straightforward.

Attention↗

PubMed2006

Heroin-related attentional bias and monthly frequency of heroin use are positively associated in attenders of a harm reduction service.

The relationship between heroin-related attentional bias (AB) and a proxy for dependence severity (monthly frequency of heroin use-injecting or inhaling) was measured in individuals attending a heroin harm reduction service. A flicker change blindness paradigm was employed in which change detection latencies were measured to either a heroin-related or to a neutral change made to a stimulus array containing an equal number of heroin-related and neutral words. Individuals given the heroin-related change to detect showed a positive relationship between heroin-related AB and the proxy for dependence severity; those given the neutral change showed a negative relationship. Both findings complement each other--and are consistent with the sending of more attention to heroin-related stimuli than neutral, the more severe is the dependence.

Adult↗

PubMed2005

Ambiguity resolution analysis in incremental parsing of natural language.

Incremental parsing gains its importance in natural language processing and psycholinguistics because of its cognitive plausibility. Modeling the associated cognitive data structures, and their dynamics, can lead to a better understanding of the human parser. In earlier work, we have introduced a recursive neural network (RNN) capable of performing syntactic ambiguity resolution in incremental parsing. In this paper, we report a systematic analysis of the behavior of the network that allows us to gain important insights about the kind of information that is exploited to resolve different forms of ambiguity. In attachment ambiguities, in which a new phrase can be attached at more than one point in the syntactic left context, we found that learning from examples allows us to predict the location of the attachment point with high accuracy, while the discrimination amongst alternative syntactic structures with the same attachment point is slightly better than making a decision purely based on frequencies. We also introduce several new ideas to enhance the architectural design, obtaining significant improvements of prediction accuracy, up to 25% error reduction on the same dataset used in previous work. Finally, we report large scale experiments on the entire Wall Street Journal section of the Penn Treebank. The best prediction accuracy of the model on this large dataset is 87.6%, a relative error reduction larger than 50% compared to previous results.

Algorithms↗

PubMed2004

Linguistic focus and good-enough representations: an application of the change-detection paradigm.

A number of lines of study suggest that word meanings are not always fully exploited in comprehension. In two experiments, we used a text-change paradigm to study depth of semantic processing during reading. Participants were instructed to detect words that changed across two consecutive presentations of short texts. The results suggest that the full details of word meanings are not always incorporated into the interpretation and that the degree of semantic detail in the representation is a function of linguistic focus. The results provide evidence for the idea that representations are only good enough for the purpose at hand (Ferreira, Bailey, & Ferraro, 2002).

Humans↗

PubMed2003

Learning first-pass structural attachment preferences with dynamic grammars and recursive neural networks.

One of the central problems in the study of human language processing is ambiguity resolution: how do people resolve the extremely pervasive ambiguity of the language they encounter? One possible answer to this question is suggested by experience-based models, which claim that people typically resolve ambiguities in a way which has been successful in the past. In order to determine the course of action that has been "successful in the past" when faced with some ambiguity, it is necessary to generalize over past experience. In this paper, we will present a computational experience-based model, which learns to generalize over linguistic experience from exposure to syntactic structures in a corpus. The model is a hybrid system, which uses symbolic grammars to build and represent syntactic structures, and neural networks to rank these structures on the basis of its experience. We use a dynamic grammar, which provides a very tight correspondence between grammatical derivations and incremental processing, and recursive neural networks, which are able to deal with the complex hierarchical structures produced by the grammar. We demonstrate that the model reproduces a number of the structural preferences found in the experimental psycholinguistics literature, and also performs well on unrestricted text.

Choice Behavior↗

PubMed2003

A new look at the syntax-discourse interface: the use of binding principles in sentence processing.

Within Generative Grammar, binding constraints on co-reference are usually defined in syntactic terms. However, some researchers have pointed out examples in which syntactically defined binding constraints do not seem to apply, proposing instead that a complete account of linguistic co-reference needs to consider notions of discourse structure. There have been several proposals in the literature for the division of labor between syntax and discourse in the definition of binding constraints. In this paper, we review these proposals in the context of recent work that applies online techniques to explore the roles of syntactic and discourse preferences in terms of the time course with which they become active during sentence comprehension. Some of this research suggests that (syntactic) binding principles may be momentarily applied during processing, even in cases in which the final interpretation suggests otherwise. We end the paper by considering the theoretical and methodological implications of this view.

Communication↗

PubMed2002

Depth of processing in language comprehension: not noticing the evidence.

The study of processes underlying the interpretation of language often produces evidence that they are complete and occur incrementally. However, computational linguistics has shown that interpretations are often effective even if they are underspecified. We present evidence that similar underspecified representations are used by humans during comprehension, drawing on a scattered and varied literature. We also show how linguistic properties of focus, subordination and focalization can control depth of processing, leading to underspecified representations. Modulation of degrees of specification might provide a way forward in the development of models of the processing underlying language understanding.

Journal Article↗