The paper presents the design and construction of a time-stamped multimodal dataset for reading research, including multiple time-aligned temporal signals elicited with four experimental trials of connected text reading by both child and adult readers. We present the experimental protocols, as well as the data acquisition process and the post-processing phase of data annotation/augmentation. To evaluate the potential and usefulness of a time-aligned multimodal dataset for reading research, we present a few statistical analyses showing the correlation and complementarity of multimodal time-series of reading data, as well as some results of modelling adults’ reading data by integrating different modalities. The total dataset size amounts to about 2.5 GByte in compressed format and is available through the CLARIN infrastructure.
ReadLet: a Dataset for Oral, Visual and Tactile Text Reading Data of Early and Mature Readers
Ferro M.Primo
;Marzi C.Secondo
;Nadalini A.;Taxitari L.;Lento A.;Pirrelli V.Ultimo
2024
Abstract
The paper presents the design and construction of a time-stamped multimodal dataset for reading research, including multiple time-aligned temporal signals elicited with four experimental trials of connected text reading by both child and adult readers. We present the experimental protocols, as well as the data acquisition process and the post-processing phase of data annotation/augmentation. To evaluate the potential and usefulness of a time-aligned multimodal dataset for reading research, we present a few statistical analyses showing the correlation and complementarity of multimodal time-series of reading data, as well as some results of modelling adults’ reading data by integrating different modalities. The total dataset size amounts to about 2.5 GByte in compressed format and is available through the CLARIN infrastructure.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.orgunit | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | en |
| dc.authority.people | Ferro M. | en |
| dc.authority.people | Marzi C. | en |
| dc.authority.people | Nadalini A. | en |
| dc.authority.people | Taxitari L. | en |
| dc.authority.people | Lento A. | en |
| dc.authority.people | Pirrelli V. | en |
| dc.authority.project | ReadLet | en |
| dc.collection.id.s | 71c7200a-7c5f-4e83-8d57-d3d2ba88f40d | * |
| dc.collection.name | 04.01 Contributo in Atti di convegno | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza.mi | 918 | * |
| dc.contributor.area | Non assegn | * |
| dc.contributor.area | Non assegn | * |
| dc.contributor.area | Non assegn | * |
| dc.contributor.area | Non assegn | * |
| dc.contributor.area | Non assegn | * |
| dc.date.accessioned | 2024/11/28 15:16:50 | - |
| dc.date.available | 2024/11/28 15:16:50 | - |
| dc.date.firstsubmission | 2024/09/25 16:15:57 | * |
| dc.date.issued | 2024 | - |
| dc.date.submission | 2025/02/28 16:39:58 | * |
| dc.description.abstracteng | The paper presents the design and construction of a time-stamped multimodal dataset for reading research, including multiple time-aligned temporal signals elicited with four experimental trials of connected text reading by both child and adult readers. We present the experimental protocols, as well as the data acquisition process and the post-processing phase of data annotation/augmentation. To evaluate the potential and usefulness of a time-aligned multimodal dataset for reading research, we present a few statistical analyses showing the correlation and complementarity of multimodal time-series of reading data, as well as some results of modelling adults’ reading data by integrating different modalities. The total dataset size amounts to about 2.5 GByte in compressed format and is available through the CLARIN infrastructure. | - |
| dc.description.allpeople | Ferro, M.; Marzi, C.; Nadalini, A.; Taxitari, L.; Lento, A.; Pirrelli, V. | - |
| dc.description.allpeopleoriginal | Ferro M.; Marzi C.; Nadalini A.; Taxitari L.; Lento A.; Pirrelli V. | en |
| dc.description.fulltext | open | en |
| dc.description.international | si | en |
| dc.description.note | ISSN 2951-2093 (COLING) ISSN 2522-2686 (LREC) | en |
| dc.description.numberofauthors | 6 | - |
| dc.identifier.isbn | 978-2-493814-10-4 | en |
| dc.identifier.scopus | 2-s2.0-85195889903 | en |
| dc.identifier.source | scopus | * |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/501843 | - |
| dc.identifier.url | https://aclanthology.org/volumes/2024.lrec-main/ | en |
| dc.language.iso | eng | en |
| dc.publisher.country | FRA | en |
| dc.publisher.name | ELRA Language Resources Association (ELRA) | en |
| dc.publisher.place | Parigi | en |
| dc.relation.allauthors | Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue | en |
| dc.relation.conferencedate | 20-25 maggio 2024 | en |
| dc.relation.conferencename | 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) | en |
| dc.relation.conferenceplace | Torino, Italia | en |
| dc.relation.firstpage | 13595 | en |
| dc.relation.ispartofbook | Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) | en |
| dc.relation.lastpage | 13609 | en |
| dc.relation.medium | ELETTRONICO | en |
| dc.relation.numberofpages | 15 | en |
| dc.relation.projectAcronym | READLET | en |
| dc.relation.projectAwardNumber | PRIN 2017W8HFRX | en |
| dc.relation.projectAwardTitle | ReadLet: Reading to understand. An ICT-driven, large-scale investigation of early grade children's reading strategies. | en |
| dc.relation.projectFunderName | MUR | en |
| dc.relation.projectFundingStream | PRIN | en |
| dc.subject.keywordseng | text reading, eye movements, finger movements, eye-finger span, synchronisation, parallel processing, multimodality | - |
| dc.subject.singlekeyword | text reading | * |
| dc.subject.singlekeyword | eye movements | * |
| dc.subject.singlekeyword | finger movements | * |
| dc.subject.singlekeyword | eye-finger span | * |
| dc.subject.singlekeyword | synchronisation | * |
| dc.subject.singlekeyword | parallel processing | * |
| dc.subject.singlekeyword | multimodality | * |
| dc.title | ReadLet: a Dataset for Oral, Visual and Tactile Text Reading Data of Early and Mature Readers | en |
| dc.type.circulation | Internazionale | en |
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| dc.type.full | 04 Contributo in convegno::04.01 Contributo in Atti di convegno | it |
| dc.type.impactfactor | si | en |
| dc.type.invited | contributo | en |
| dc.type.miur | 273 | - |
| dc.type.referee | Esperti anonimi | en |
| iris.mediafilter.data | 2025/04/06 03:11:07 | * |
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| iris.scopus.extIssued | 2024 | - |
| iris.scopus.extTitle | ReadLet: a Dataset for Oral, Visual and Tactile Text Reading Data of Early and Mature Readers | - |
| iris.scopus.ideLinkStatusDate | 2024/09/27 18:29:06 | * |
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| scopus.category | 2614 | * |
| scopus.category | 1706 | * |
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| scopus.contributor.affiliation | Institute for Computational Linguistics | - |
| scopus.contributor.affiliation | Institute for Computational Linguistics | - |
| scopus.contributor.affiliation | Institute for Computational Linguistics | - |
| scopus.contributor.affiliation | Neapolis University | - |
| scopus.contributor.affiliation | Biomedical Campus University | - |
| scopus.contributor.affiliation | Institute for Computational Linguistics | - |
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| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Cyprus | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
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| scopus.contributor.name | Alessandro | - |
| scopus.contributor.name | Vito | - |
| scopus.contributor.subaffiliation | Italian National Research Council; | - |
| scopus.contributor.subaffiliation | Italian National Research Council; | - |
| scopus.contributor.subaffiliation | Italian National Research Council; | - |
| scopus.contributor.subaffiliation | Department of Psychology; | - |
| scopus.contributor.subaffiliation | - | |
| scopus.contributor.subaffiliation | Italian National Research Council; | - |
| scopus.contributor.surname | Ferro | - |
| scopus.contributor.surname | Marzi | - |
| scopus.contributor.surname | Nadalini | - |
| scopus.contributor.surname | Taxitari | - |
| scopus.contributor.surname | Lento | - |
| scopus.contributor.surname | Pirrelli | - |
| scopus.date.issued | 2024 | * |
| scopus.description.abstracteng | The paper presents a time-stamped multimodal dataset for reading research, including multiple time-aligned temporal signals elicited with four experimental trials of connected text reading by both child and adult readers. We illustrate design issues and experimental protocols, as well as the data acquisition process and the post-processing phase of data annotation/augmentation. To evaluate the potential and usefulness of a time-aligned multimodal dataset for reading research, we present a few statistical analyses showing the correlation and complementarity of multimodal time-series of reading data, as well as some results of modelling adults' reading data by integrating different modalities. The total dataset size amounts to about 2.5 GByte in compressed format and is available through the CLARIN infrastructure. | * |
| scopus.description.allpeopleoriginal | Ferro M.; Marzi C.; Nadalini A.; Taxitari L.; Lento A.; Pirrelli V. | * |
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| scopus.publisher.name | European Language Resources Association (ELRA) | * |
| scopus.relation.conferencedate | 2024 | * |
| scopus.relation.conferencename | Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024 | * |
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| scopus.relation.firstpage | 13595 | * |
| scopus.relation.lastpage | 13609 | * |
| scopus.subject.keywords | eye movements; eye-finger span; finger movements; multimodality; parallel processing; synchronisation; text reading; | * |
| scopus.title | ReadLet: a Dataset for Oral, Visual and Tactile Text Reading Data of Early and Mature Readers | * |
| scopus.titleeng | ReadLet: a Dataset for Oral, Visual and Tactile Text Reading Data of Early and Mature Readers | * |
| Appare nelle tipologie: | 04.01 Contributo in Atti di convegno | |
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