Human and computer estimations of predictability of words on written language

Autores
Bianchi, Bruno; Carrillo, Facundo; Fernández Slezak, Diego; Kamienkowski, Juan E.; Shalom, Diego E.
Año de publicación
2014
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
When we read printed text, we continuously predict the follow words in order to integrate information and direct future eye movements to forthcoming words. Thus the Predictability has become one the most important variables when explaining human behavior and information processing during reading. In this study we present results of word predictability in long Spanish texts, estimated from human responses in a massive web-based task. We used Latent Semantic Analysis (LSA) as a way to estimate human-based predictability values computationally. We validated the human estimation of predictability with local and global properties of the text, and we showed that LSA-distance on adequate timescale captures some semantic aspects of the prediction.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Inteligencia Artificial
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/41731
Acceder
id SEDICI_752c4cfbb3472a84aba105c6be14666a
oai_identifier_str oai:sedici.unlp.edu.ar:10915/41731
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Human and computer estimations of predictability of words on written languageBianchi, BrunoCarrillo, FacundoFernández Slezak, DiegoKamienkowski, Juan E.Shalom, Diego E.Ciencias InformáticasInteligencia ArtificialWhen we read printed text, we continuously predict the follow words in order to integrate information and direct future eye movements to forthcoming words. Thus the Predictability has become one the most important variables when explaining human behavior and information processing during reading. In this study we present results of word predictability in long Spanish texts, estimated from human responses in a massive web-based task. We used Latent Semantic Analysis (LSA) as a way to estimate human-based predictability values computationally. We validated the human estimation of predictability with local and global properties of the text, and we showed that LSA-distance on adequate timescale captures some semantic aspects of the prediction.Sociedad Argentina de Informática e Investigación Operativa2014-11info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf99-106http://sedici.unlp.edu.ar/handle/10915/41731enginfo:eu-repo/semantics/altIdentifier/url/http://43jaiio.sadio.org.ar/proceedings/ASAI/13.pdfinfo:eu-repo/semantics/altIdentifier/issn/1850-2784info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/Creative Commons Attribution 3.0 Unported (CC BY 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:42:41Zoai:sedici.unlp.edu.ar:10915/41731Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:42:41.499SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Human and computer estimations of predictability of words on written language
title Human and computer estimations of predictability of words on written language
spellingShingle Human and computer estimations of predictability of words on written language
Bianchi, Bruno
Ciencias Informáticas
Inteligencia Artificial
title_short Human and computer estimations of predictability of words on written language
title_full Human and computer estimations of predictability of words on written language
title_fullStr Human and computer estimations of predictability of words on written language
title_full_unstemmed Human and computer estimations of predictability of words on written language
title_sort Human and computer estimations of predictability of words on written language
dc.creator.none.fl_str_mv Bianchi, Bruno
Carrillo, Facundo
Fernández Slezak, Diego
Kamienkowski, Juan E.
Shalom, Diego E.
author Bianchi, Bruno
author_facet Bianchi, Bruno
Carrillo, Facundo
Fernández Slezak, Diego
Kamienkowski, Juan E.
Shalom, Diego E.
author_role author
author2 Carrillo, Facundo
Fernández Slezak, Diego
Kamienkowski, Juan E.
Shalom, Diego E.
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Inteligencia Artificial
topic Ciencias Informáticas
Inteligencia Artificial
dc.description.none.fl_txt_mv When we read printed text, we continuously predict the follow words in order to integrate information and direct future eye movements to forthcoming words. Thus the Predictability has become one the most important variables when explaining human behavior and information processing during reading. In this study we present results of word predictability in long Spanish texts, estimated from human responses in a massive web-based task. We used Latent Semantic Analysis (LSA) as a way to estimate human-based predictability values computationally. We validated the human estimation of predictability with local and global properties of the text, and we showed that LSA-distance on adequate timescale captures some semantic aspects of the prediction.
Sociedad Argentina de Informática e Investigación Operativa
description When we read printed text, we continuously predict the follow words in order to integrate information and direct future eye movements to forthcoming words. Thus the Predictability has become one the most important variables when explaining human behavior and information processing during reading. In this study we present results of word predictability in long Spanish texts, estimated from human responses in a massive web-based task. We used Latent Semantic Analysis (LSA) as a way to estimate human-based predictability values computationally. We validated the human estimation of predictability with local and global properties of the text, and we showed that LSA-distance on adequate timescale captures some semantic aspects of the prediction.
publishDate 2014
dc.date.none.fl_str_mv 2014-11
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/41731
url http://sedici.unlp.edu.ar/handle/10915/41731
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://43jaiio.sadio.org.ar/proceedings/ASAI/13.pdf
info:eu-repo/semantics/altIdentifier/issn/1850-2784
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
dc.format.none.fl_str_mv application/pdf
99-106
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1846782921441017856
score 12.982451

Publicaciones similares