7 research outputs found
Role of expectation and working memory constraints in Hindi comprehension: An eyetracking corpus analysis
We used the Potsdam-Allahabad Hindi eye-tracking corpus to investigate the role of word-level and sentence-level factors during sentence comprehension in Hindi. Extending previous work that used this eye-tracking data, we investigate the role of surprisal and retrieval cost metrics during sentence processing. While controlling for word-level predictors (word complexity, syllable length, unigram and bigram frequencies) as well as sentence-level predictors such as integration and storage costs, we find a significant effect of surprisal on first-pass reading times (higher surprisal value leads to increase in FPRT). Effect of retrieval cost was only found for a higher degree of parser parallelism. Interestingly, while surprisal has a significant effect on FPRT, storage cost (another prediction-based metric) does not. A significant effect of storage cost shows up only in total fixation time (TFT), thus indicating that these two measures perhaps capture different aspects of prediction. The study replicates previous findings that both prediction-based and memory-based metrics are required to account for processing patterns during sentence comprehension. The results also show that parser model assumptions are critical in order to draw generalizations about the utility of a metric (e.g. surprisal) across various phenomena in a language
An Unsolicited Soliloquy on Dependency Parsing
Programa Oficial de Doutoramento en Computación . 5009V01[Abstract]
This thesis presents work on dependency parsing covering two distinct lines of research. The
first aims to develop efficient parsers so that they can be fast enough to parse large amounts
of data while still maintaining decent accuracy. We investigate two techniques to achieve
this. The first is a cognitively-inspired method and the second uses a model distillation
method. The first technique proved to be utterly dismal, while the second was somewhat of
a success.
The second line of research presented in this thesis evaluates parsers. This is also done in
two ways. We aim to evaluate what causes variation in parsing performance for different
algorithms and also different treebanks. This evaluation is grounded in dependency displacements
(the directed distance between a dependent and its head) and the subsequent
distributions associated with algorithms and the distributions found in treebanks. This work
sheds some light on the variation in performance for both different algorithms and different
treebanks. And the second part of this area focuses on the utility of part-of-speech tags
when used with parsing systems and questions the standard position of assuming that they
might help but they certainly won’t hurt.[Resumen]
Esta tesis presenta trabajo sobre análisis de dependencias que cubre dos lÃneas de investigación distintas. La primera tiene como objetivo desarrollar analizadores eficientes, de
modo que sean suficientemente rápidos como para analizar grandes volúmenes de datos y,
al mismo tiempo, sean suficientemente precisos. Investigamos dos métodos. El primero se
basa en teorÃas cognitivas y el segundo usa una técnica de destilación. La primera técnica
resultó un enorme fracaso, mientras que la segunda fue en cierto modo un ´éxito.
La otra lÃnea evalúa los analizadores sintácticos. Esto también se hace de dos maneras. Evaluamos
la causa de la variación en el rendimiento de los analizadores para distintos algoritmos
y corpus. Esta evaluación utiliza la diferencia entre las distribuciones del desplazamiento
de arista (la distancia dirigida de las aristas) correspondientes a cada algoritmo y corpus.
También evalúa la diferencia entre las distribuciones del desplazamiento de arista en los
datos de entrenamiento y prueba. Este trabajo esclarece las variaciones en el rendimiento
para algoritmos y corpus diferentes. La segunda parte de esta lÃnea investiga la utilidad de
las etiquetas gramaticales para los analizadores sintácticos.[Resumo]
Esta tese presenta traballo sobre análise sintáctica, cubrindo dúas liñas de investigación. A
primeira aspira a desenvolver analizadores eficientes, de maneira que sexan suficientemente
rápidos para procesar grandes volumes de datos e á vez sexan precisos. Investigamos dous
métodos. O primeiro baséase nunha teorÃa cognitiva, e o segundo usa unha técnica de
destilación. O primeiro método foi un enorme fracaso, mentres que o segundo foi en certo
modo un éxito.
A outra liña avalúa os analizadores sintácticos. Esto tamén se fai de dúas maneiras. Avaliamos
a causa da variación no rendemento dos analizadores para distintos algoritmos e corpus. Esta
avaliaci´on usa a diferencia entre as distribucións do desprazamento de arista (a distancia
dirixida das aristas) correspondentes aos algoritmos e aos corpus. Tamén avalÃa a diferencia
entre as distribucións do desprazamento de arista nos datos de adestramento e proba.
Este traballo esclarece as variacións no rendemento para algoritmos e corpus diferentes. A
segunda parte desta liña investiga a utilidade das etiquetas gramaticais para os analizadores
sintácticos.This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (FASTPARSE, grant agreement No 714150) and from the Centro de Investigación de Galicia (CITIC) which is funded by the Xunta de Galicia and the European Union (ERDF - Galicia 2014-2020 Program) by grant ED431G 2019/01.Xunta de Galicia; ED431G 2019/0
Comparing the production of a formula with the development of L2 competence
This pilot study investigates the production of a formula with the development of L2 competence over proficiency levels of a spoken learner corpus. The results show that the formula
in beginner production data is likely being recalled holistically from learners’ phonological
memory rather than generated online, identifiable by virtue of its fluent production in absence
of any other surface structure evidence of the formula’s syntactic properties. As learners’ L2
competence increases, the formula becomes sensitive to modifications which show structural
conformity at each proficiency level. The transparency between the formula’s modification
and learners’ corresponding L2 surface structure realisations suggest that it is the independent
development of L2 competence which integrates the formula into compositional language,
and ultimately drives the SLA process forward