TY  - JOUR
A1  - Laurinavichyute, Anna
A1  - Sekerina, Irina A.
A1  - Alexeeva, Svetlana
A1  - Bagdasaryan, Kristine
A1  - Kliegl, Reinhold
T1  - Russian Sentence Corpus: Benchmark measures of eye movements in reading in Russian
JF  - Behavior research methods : a journal of the Psychonomic Society
N2  - This article introduces a new corpus of eye movements in silent readingthe Russian Sentence Corpus (RSC). Russian uses the Cyrillic script, which has not yet been investigated in cross-linguistic eye movement research. As in every language studied so far, we confirmed the expected effects of low-level parameters, such as word length, frequency, and predictability, on the eye movements of skilled Russian readers. These findings allow us to add Slavic languages using Cyrillic script (exemplified by Russian) to the growing number of languages with different orthographies, ranging from the Roman-based European languages to logographic Asian ones, whose basic eye movement benchmarks conform to the universal comparative science of reading (Share, 2008). We additionally report basic descriptive corpus statistics and three exploratory investigations of the effects of Russian morphology on the basic eye movement measures, which illustrate the kinds of questions that researchers can answer using the RSC. The annotated corpus is freely available from its project page at the Open Science Framework: https://osf.io/x5q2r/.
KW  - Reading
KW  - Eye movements
KW  - Russian
KW  - Ambiguity
KW  - Part of speech
KW  - Corpus
Y1  - 2019
U6  - https://doi.org/10.3758/s13428-018-1051-6
SN  - 1554-351X
SN  - 1554-3528
VL  - 51
IS  - 3
SP  - 1161
EP  - 1178
PB  - Springer
CY  - New York
ER  - 
TY  - JOUR
A1  - Logacev, Pavel
A1  - Vasishth, Shravan
T1  - A Multiple-Channel Model of Task-Dependent Ambiguity Resolution in Sentence Comprehension
JF  - Cognitive science : a multidisciplinary journal of anthropology, artificial intelligence, education, linguistics, neuroscience, philosophy, psychology ; journal of the Cognitive Science Society
N2  - Traxler, Pickering, and Clifton (1998) found that ambiguous sentences are read faster than their unambiguous counterparts. This so-called ambiguity advantage has presented a major challenge to classical theories of human sentence comprehension (parsing) because its most prominent explanation, in the form of the unrestricted race model (URM), assumes that parsing is non-deterministic. Recently, Swets, Desmet, Clifton, and Ferreira (2008) have challenged the URM. They argue that readers strategically underspecify the representation of ambiguous sentences to save time, unless disambiguation is required by task demands. When disambiguation is required, however, readers assign sentences full structure—and Swets et al. provide experimental evidence to this end. On the basis of their findings, they argue against the URM and in favor of a model of task-dependent sentence comprehension. We show through simulations that the Swets et al. data do not constitute evidence for task-dependent parsing because they can be explained by the URM. However, we provide decisive evidence from a German self-paced reading study consistent with Swets et al.'s general claim about task-dependent parsing. Specifically, we show that under certain conditions, ambiguous sentences can be read more slowly than their unambiguous counterparts, suggesting that the parser may create several parses, when required. Finally, we present the first quantitative model of task-driven disambiguation that subsumes the URM, and we show that it can explain both Swets et al.'s results and our findings.
KW  - Sentence processing
KW  - Ambiguity
KW  - Parallel processing
KW  - Cognitive modeling
KW  - Unrestricted race model
KW  - URM
KW  - Underspecification
KW  - Good-enough processing
Y1  - 2016
U6  - https://doi.org/10.1111/cogs.12228
SN  - 0364-0213
SN  - 1551-6709
VL  - 40
SP  - 266
EP  - 298
PB  - Wiley-Blackwell
CY  - Hoboken
ER  -