LSA-T: The First Continuous Argentinian Sign Language Dataset for Sign Language Translation

被引：6

作者：

Dal Bianco, Pedro ^{[1
,3
]}

Rios, Gaston ^{[1
,3
]}

Ronchetti, Franco ^{[1
,2
]}

Quiroga, Facundo ^{[1
,3
]}

Stanchi, Oscar ^{[1
]}

Hasperue, Waldo ^{[1
,2
]}

Rosete, Alejandro ^{[4
]}

机构：

[1] Univ Nacl La Plata, Inst Invest Informat LIDI, La Plata, Argentina

[2] CIC PBA, La Plata, Argentina

[3] UNLP, La Plata, Argentina

[4] Univ Tecnol La Habana Jose Antonio Echeverria, Havana, Cuba

来源：

ADVANCES IN ARTIFICIAL INTELLIGENCE-IBERAMIA 2022 | 2022年 / 13788卷

关键词：

Sign Language Translation; Computer vision; Big data; Sign language dataset; Deep learning;

D O I：

10.1007/978-3-031-22419-5_25

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Sign language translation (SLT) is an active field of study that encompasses human-computer interaction, computer vision, natural language processing and machine learning. Progress on this field could lead to higher levels of integration of deaf people. This paper presents, to the best of our knowledge, the first continuous Argentinian Sign Language (LSA) dataset. It contains 14,880 sentence level videos of LSA extracted from the CN Sordos YouTube channel with labels and keypoints annotations for each signer. We also present a method for inferring the active signer, a detailed analysis of the characteristics of the dataset, a visualization tool to explore the dataset and a neural SLT model to serve as baseline for future experiments.

引用

页码：293 / 304

页数：12

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