@inproceedings{belcavello-etal-2024-frame2-framenet,
title = "Frame2: A {F}rame{N}et-based Multimodal Dataset for Tackling Text-image Interactions in Video",
author = "Belcavello, Frederico and
Timponi Torrent, Tiago and
Matos, Ely E. and
Pagano, Adriana S. and
Gamonal, Maucha and
Sigiliano, Natalia and
Dutra, L{\'\i}via Vicente and
de Andrade Abreu, Helen and
Samagaio, Mairon and
Carvalho, Mariane and
Campos, Franciany and
Azalim, Gabrielly and
Mazzei, Bruna and
de Oliveira, Mateus Fonseca and
Lo{\c{c}}asso Luz, Ana Carolina and
P{\'a}dua Ruiz, L{\'\i}via and
Bellei, J{\'u}lia and
Pestana, Amanda and
Costa, Josiane and
Rabelo, Iasmin and
Silva, Anna Beatriz and
Roza, Raquel and
Souza, Mariana and
Oliveira, Igor",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.655",
pages = "7429--7437",
abstract = "This paper presents the Frame2 dataset, a multimodal dataset built from a corpus of a Brazilian travel TV show annotated for FrameNet categories for both the text and image communicative modes. Frame2 comprises 230 minutes of video, which are correlated with 2,915 sentences either transcribing the audio spoken during the episodes or the subtitling segments of the show where the host conducts interviews in English. For this first release of the dataset, a total of 11,796 annotation sets for the sentences and 6,841 for the video are included. Each of the former includes a target lexical unit evoking a frame or one or more frame elements. For each video annotation, a bounding box in the image is correlated with a frame, a frame element and lexical unit evoking a frame in FrameNet.",
}
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<abstract>This paper presents the Frame2 dataset, a multimodal dataset built from a corpus of a Brazilian travel TV show annotated for FrameNet categories for both the text and image communicative modes. Frame2 comprises 230 minutes of video, which are correlated with 2,915 sentences either transcribing the audio spoken during the episodes or the subtitling segments of the show where the host conducts interviews in English. For this first release of the dataset, a total of 11,796 annotation sets for the sentences and 6,841 for the video are included. Each of the former includes a target lexical unit evoking a frame or one or more frame elements. For each video annotation, a bounding box in the image is correlated with a frame, a frame element and lexical unit evoking a frame in FrameNet.</abstract>
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%0 Conference Proceedings
%T Frame2: A FrameNet-based Multimodal Dataset for Tackling Text-image Interactions in Video
%A Belcavello, Frederico
%A Timponi Torrent, Tiago
%A Matos, Ely E.
%A Pagano, Adriana S.
%A Gamonal, Maucha
%A Sigiliano, Natalia
%A Dutra, Lívia Vicente
%A de Andrade Abreu, Helen
%A Samagaio, Mairon
%A Carvalho, Mariane
%A Campos, Franciany
%A Azalim, Gabrielly
%A Mazzei, Bruna
%A de Oliveira, Mateus Fonseca
%A Loçasso Luz, Ana Carolina
%A Pádua Ruiz, Lívia
%A Bellei, Júlia
%A Pestana, Amanda
%A Costa, Josiane
%A Rabelo, Iasmin
%A Silva, Anna Beatriz
%A Roza, Raquel
%A Souza, Mariana
%A Oliveira, Igor
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F belcavello-etal-2024-frame2-framenet
%X This paper presents the Frame2 dataset, a multimodal dataset built from a corpus of a Brazilian travel TV show annotated for FrameNet categories for both the text and image communicative modes. Frame2 comprises 230 minutes of video, which are correlated with 2,915 sentences either transcribing the audio spoken during the episodes or the subtitling segments of the show where the host conducts interviews in English. For this first release of the dataset, a total of 11,796 annotation sets for the sentences and 6,841 for the video are included. Each of the former includes a target lexical unit evoking a frame or one or more frame elements. For each video annotation, a bounding box in the image is correlated with a frame, a frame element and lexical unit evoking a frame in FrameNet.
%U https://aclanthology.org/2024.lrec-main.655
%P 7429-7437
Markdown (Informal)
[Frame2: A FrameNet-based Multimodal Dataset for Tackling Text-image Interactions in Video](https://aclanthology.org/2024.lrec-main.655) (Belcavello et al., LREC-COLING 2024)
ACL
- Frederico Belcavello, Tiago Timponi Torrent, Ely E. Matos, Adriana S. Pagano, Maucha Gamonal, Natalia Sigiliano, Lívia Vicente Dutra, Helen de Andrade Abreu, Mairon Samagaio, Mariane Carvalho, Franciany Campos, Gabrielly Azalim, Bruna Mazzei, Mateus Fonseca de Oliveira, Ana Carolina Loçasso Luz, Lívia Pádua Ruiz, Júlia Bellei, Amanda Pestana, Josiane Costa, et al.. 2024. Frame2: A FrameNet-based Multimodal Dataset for Tackling Text-image Interactions in Video. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 7429–7437, Torino, Italia. ELRA and ICCL.