Artículo
Human and computer estimations of Predictability of words in written language
Bianchi, Bruno
; Bengolea Monzón, Gastón; Ferrer, Luciana
; Fernández Slezak, Diego; Shalóm, Diego Edgar
; Kamienkowski, Juan Esteban
Fecha de publicación:
10/03/2020
Editorial:
Nature Research
Revista:
Scientific Reports
ISSN:
2045-2322
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
When we read printed text, we are continuously predicting upcoming words to integrate information and guide future eye movements. Thus, the Predictability of a given word has become one of the most important variables when explaining human behaviour and information processing during reading. In parallel, the Natural Language Processing (NLP) field evolved by developing a wide variety of applications. Here, we show that using different word embeddings techniques (like Latent Semantic Analysis, Word2Vec, and FastText) and N-gram-based language models we were able to estimate how humans predict words (cloze-task Predictability) and how to better understand eye movements in long Spanish texts. Both types of models partially captured aspects of predictability. On the one hand, our N-gram model performed well when added as a replacement for the cloze-task Predictability of the fixated word. On the other hand, word embeddings were useful to mimic Predictability of the following word. Our study joins efforts from neurolinguistic and NLP fields to understand human information processing during reading to potentially improve NLP algorithms.
Palabras clave:
Predictability
,
Eye Movements
,
Natural Language Processing
,
Reading
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Articulos de INSTITUTO DE INVESTIGACION EN CIENCIAS DE LA COMPUTACION
Articulos de INSTITUTO DE INVESTIGACION EN CIENCIAS DE LA COMPUTACION
Citación
Bianchi, Bruno; Bengolea Monzón, Gastón; Ferrer, Luciana; Fernández Slezak, Diego; Shalóm, Diego Edgar; et al.; Human and computer estimations of Predictability of words in written language; Nature Research; Scientific Reports; 10; 1; 10-3-2020; 1-11
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