Hongoak Yun

Semantic similarity, predictability, and models of sentence processing

The effects of word predictability and shared semantic similarity between a target word and other words that could have taken its place in a sentence on language comprehension are investigated using data from a reading time study, a sentence completion study, and linear mixed-effects regression modeling. We find that processing is facilitated if the different possible words that could occur in a given context are semantically similar to each other, meaning that processing is affected not only by the nature of the words that do occur, but also the relationships between the words that do occur and those that could have occurred. We discuss possible causes of the semantic similarity effect and point to possible limitations of using probability as a model of cognitive effort.

Which Event Properties Matter for Which Cognitive Task

Two important questions in the language sciences have been: What portion of event information is accessed and used during sentence processing? What portion of event information is relevant to the grammar of natural languages? An extensive amount of linguistic and psycholinguistic research over the past couple of decades has shown that quite a bit of event information is relevant to online sentence processing, but only a limited amount of information is relevant to the grammars of natural languages. One possible cause for this divergence is that grammar development and language comprehension are carried out by separate systems that are sensitive to different types of information. Another possible explanation is that grammar development and language comprehension are carried out by an integrated system, but the task demands of language learning and the task demands of language comprehension are different. In this chapter, we show that, grammatical systems that seem more “exotic” from the point of view of more well-known languages still make use of a limited set of properties and that these “exotic” languages still obey the same design constraints as more well-known systems; we then briefly report on some computational models of online reading experiments, which demonstrate quite clearly that a distinct and much larger kind of event knowledge is used by the human parser. We propose an explanation for this difference in the use of event knowledge: Grammars and parsers use different kinds of event knowledge because the tasks listeners and grammar learners must perform are quite distinct.

The predictability effect on eye movement in reading Korean dative sentences

Yun and Hong (2014) demonstrated the effect of role predictability and word predictability in the processing of Korean dative sentences. We aimed to investigate the nature of predictability effect that Yun and Hong observed, in particular, to explore whether the effect would reflect the early stage or the late stage of processing by observing readers` eye movement in reading. The significant effect of role predictability and word predictability were addictively observed in the measurement of early processing (i.e., first pass reading times) but not in the measurement of late processing (i.e., regression rates). Of interest, the effect of word predictability was mainly based on the processing of words of low role predictability. Our results indicate that when a thematic role for an upcoming word is not highly expected, word predictability contributes to the reduction of readers` integration difficulty, in a way that more predictable word is easier to be integrated into a sentence. We discuss our results in terms of Staub`s (2015) theoretical conclusion that the predictability effect depends on the process that multiple words are activated at once at graded degrees from the early stage. (Gachon University and Konkuk University)