AzSLD: Azerbaijani sign language dataset for fingerspelling, word, and sentence translation with baseline softwareZenodo
Advancements in sign language processing technology hinge on the availability of extensive, reliable datasets, comprehensive instructions, and adherence to ethical guidelines. To facilitate progress in gesture recognition and translation systems and to support the Azerbaijani sign language community...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Data in Brief |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340924011922 |
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| author | Nigar Alishzade Jamaladdin Hasanov |
| author_facet | Nigar Alishzade Jamaladdin Hasanov |
| author_sort | Nigar Alishzade |
| collection | DOAJ |
| description | Advancements in sign language processing technology hinge on the availability of extensive, reliable datasets, comprehensive instructions, and adherence to ethical guidelines. To facilitate progress in gesture recognition and translation systems and to support the Azerbaijani sign language community we present the Azerbaijani Sign Language Dataset (AzSLD). This comprehensive dataset was collected from a diverse group of sign language users, encompassing a range of linguistic parameters. Developed within the framework of a vision-based Azerbaijani Sign Language translation project, AzSLD includes recordings of the fingerspelling alphabet, individual words, and sentences. The data acquisition process involved recording signers across various age groups, genders, and proficiency levels to ensure broad representation. Sign language sentences were captured using two cameras from different angles, providing comprehensive visual coverage of each gesture. This approach enables robust training and evaluation of gesture recognition algorithms. The dataset comprises 30,000 meticulously annotated videos, each labeled with precise gesture identifiers and corresponding linguistic translations. To facilitate efficient usage of the dataset, we provide technical instructions and source code for a data loader. Researchers and developers working on sign language recognition, translation, and synthesis systems will find AzSLD invaluable, as it offers a rich repository of labeled data for training and evaluation purposes. |
| format | Article |
| id | doaj-art-7180e15627ac4e0eae3875ba18897710 |
| institution | Kabale University |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-7180e15627ac4e0eae3875ba188977102025-01-31T05:11:35ZengElsevierData in Brief2352-34092025-02-0158111230AzSLD: Azerbaijani sign language dataset for fingerspelling, word, and sentence translation with baseline softwareZenodoNigar Alishzade0Jamaladdin Hasanov1Azerbaijan State Oil and Industry University, Baku, Azerbaijan; Institute of Control Systems, Baku, Azerbaijan; Corresponding author at: Azerbaijan State Oil and Industry University, Baku, Azerbaijan.ADA University, Baku, AzerbaijanAdvancements in sign language processing technology hinge on the availability of extensive, reliable datasets, comprehensive instructions, and adherence to ethical guidelines. To facilitate progress in gesture recognition and translation systems and to support the Azerbaijani sign language community we present the Azerbaijani Sign Language Dataset (AzSLD). This comprehensive dataset was collected from a diverse group of sign language users, encompassing a range of linguistic parameters. Developed within the framework of a vision-based Azerbaijani Sign Language translation project, AzSLD includes recordings of the fingerspelling alphabet, individual words, and sentences. The data acquisition process involved recording signers across various age groups, genders, and proficiency levels to ensure broad representation. Sign language sentences were captured using two cameras from different angles, providing comprehensive visual coverage of each gesture. This approach enables robust training and evaluation of gesture recognition algorithms. The dataset comprises 30,000 meticulously annotated videos, each labeled with precise gesture identifiers and corresponding linguistic translations. To facilitate efficient usage of the dataset, we provide technical instructions and source code for a data loader. Researchers and developers working on sign language recognition, translation, and synthesis systems will find AzSLD invaluable, as it offers a rich repository of labeled data for training and evaluation purposes.http://www.sciencedirect.com/science/article/pii/S2352340924011922Sign language datasetSign language recognitionSign language translationLarge-lexicon dataset |
| spellingShingle | Nigar Alishzade Jamaladdin Hasanov AzSLD: Azerbaijani sign language dataset for fingerspelling, word, and sentence translation with baseline softwareZenodo Data in Brief Sign language dataset Sign language recognition Sign language translation Large-lexicon dataset |
| title | AzSLD: Azerbaijani sign language dataset for fingerspelling, word, and sentence translation with baseline softwareZenodo |
| title_full | AzSLD: Azerbaijani sign language dataset for fingerspelling, word, and sentence translation with baseline softwareZenodo |
| title_fullStr | AzSLD: Azerbaijani sign language dataset for fingerspelling, word, and sentence translation with baseline softwareZenodo |
| title_full_unstemmed | AzSLD: Azerbaijani sign language dataset for fingerspelling, word, and sentence translation with baseline softwareZenodo |
| title_short | AzSLD: Azerbaijani sign language dataset for fingerspelling, word, and sentence translation with baseline softwareZenodo |
| title_sort | azsld azerbaijani sign language dataset for fingerspelling word and sentence translation with baseline softwarezenodo |
| topic | Sign language dataset Sign language recognition Sign language translation Large-lexicon dataset |
| url | http://www.sciencedirect.com/science/article/pii/S2352340924011922 |
| work_keys_str_mv | AT nigaralishzade azsldazerbaijanisignlanguagedatasetforfingerspellingwordandsentencetranslationwithbaselinesoftwarezenodo AT jamaladdinhasanov azsldazerbaijanisignlanguagedatasetforfingerspellingwordandsentencetranslationwithbaselinesoftwarezenodo |