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The American Sign Language alphabet

Description

The American Sign Language dataset contains all static letters of the American alphabet, meaning those that do not require movement to perform (the entire alphabet except for the letters 'J' and 'Z', which are dynamic and require hand movement).

Dataset Structure

The dataset is organized into 24 folders, each named after a corresponding American Sign Language alphabet letter. For example, the folder named "A" contains recordings of gestures representing the letter "A" in sign language.

Folder Contents

Each folder contains numerous video recordings of gestures corresponding to the respective letter. These recordings vary in length and quality, ensuring a diverse data set for analysis. The recordings show either a person performing the letter gesture or just the hand (some recordings feature only the hand making the gesture).

Dataset Applications

The dataset is ideal for a variety of applications, such as:

  • Training gesture recognition models: The diversity of recordings allows for the creation of robust models capable of accurately recognizing letters of the American Sign Language
    alphabet.
  • Research on sign language: It can serve as a database for studies on gesture recognition and interpretation.

Technical Specifications

  • Recording format: All recordings are in video format.
  • Recording length: Varies, providing a wide range of data for analysis.
  • Recording quality: Diverse, allowing for testing models in different conditions.
  • Content: Gestures are shown to the camera at varying distances, angles, and positions relative to the center of the screen.

Dataset file

data.zip
450.2 MB, S3 ETag 61ffdf9add2b6559e3f0626ac3a663b7-1, downloads: 0
The file hash is calculated from the formula
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.

Example script for calculation:
https://github.com/antespi/s3md5
download file data.zip

File details

License:
Creative Commons: 0 1.0 open in new tab
CC 0
Public Domain Dedication
Raw data:
Data contained in dataset was not processed.

Details

Year of publication:
2024
Verification date:
2024-07-30
Dataset language:
English
Fields of science:
  • information and communication technology (Engineering and Technology)
DOI:
DOI ID 10.34808/ctjj-fw17 open in new tab
Verified by:
Gdańsk University of Technology

Keywords

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