Sign Language Translation (SLR) is the task of automatically recognising signs from video sequences of sign language. It has significant importance as it can provide a means of communication for people with hearing or speech impairments, as well as facilitating communication between hearing and deaf communities.

Auslan is the sign language used by Australian Deaf and Hard of Hearing (DHoH) community. Coding Fest 2024 organises an AI for Auslan challenge to seek innovative AI solutions to help better communication between DHoH community and the hearing community.

This is a great opportunity to strengthen and practice your AI skills for social good. There may also be an opportunity for academic publications.

Dataset

1. Folders and Diles
• train - Training set
• test - Test set
• train.csv - Training set labels
• submission.csv - Submission example

(We use the performance on private test set for ranking.)

2. Data Description

The data we use is from a TV series named ‘Sally & Possum’. Australian Sign Language (Auslan) is used in this show. ( https://iview.abc.net.au/show/sally-and-possum)
There are 13214 videos included in the training dataset. You need to split the training and validation set if necessary. The subtitle for each clip and ‘video-clip-name’ are provided inside the .csv file.

video-clip-name: str, Clipped video ID.
subtitle: str, Auslan of clipped video.
The dataset can be downloaded in Google Drive: https://drive.google.com/drive/folders/1w_MOEjqTbI6DZB03c_vxoaGXNaF4GB06

Eligibility

• A team consists of up to 4 members and each member must be enrolled in the University of Sydney.
• The team needs to have strong programming skills. Python is preferred.
• The team is required to showcase their method in Coding Fest on 23 July.

Awards

• TBD

Timeline

1. Application
• Fill this form with your team information.
• You will receive instructions on participating in the challenges, which will include details about datasets and benchmarking.
2. Coaching
• Two coaching Meetups will be organized, and the dates of Meetups will be announced later.
• The two coaching sessions aim to provide basic and hands-on knowledge on deep learning and participation in the challenge.
• Tutorial Recording: Watch the Tutorial (Passcode: U?&An5$^)
3. Submission Deadline: 19 July 2024
4. Project showcase and Awards Ceremony will be held on 23 July 2024.

AI Auslan Organization Team

• Xin Yu (xin.yu@uq.edu.au), School of Information Technology and Electrical Engineering, Faculty of Engineering, The University of Queensland
• Xin Shen (x.shen3@uqconnect.edu.au), School of Information Technology and Electrical Engineering, Faculty of Engineering, The University of Queensland
• Siyu Xu (sixu8492@uni.sydney.edu.au), School of Computer Science, Faculty of Engineering, The University of Sydney
• Tao Huang (t.huang@sydney.edu.au), School of Computer Science, Faculty of Engineering, The University of Sydney

For any enquiries, please contact: codingfest.top@gmail.com or AI Auslan Organization Team members.

Coding Fest Organization Team

• A/Prof. Chang Xu (c.xu@sydney.edu.au), School of Computer Science, Faculty of Engineering, The University of Sydney
• Dr. Ying Zhou (ying.zhou@sydney.edu.au), School of Computer Science, Faculty of Engineering, The University of Sydney
• Dr. Mohammad Polash (masbaul.polash@sydney.edu.au), School of Computer Science, Faculty of Engineering, The University of Sydney
• Dr. Basem Suleiman (Basem.Suleiman@sydney.edu.au), School of Computer Science, Faculty of Engineering, The University of Sydney
• Porf. Zhiyong Wang (zhiyong.wang@sydney.edu.au), School of Computer Science, Faculty of Engineering, The University of Sydney

Other Links

• Coding Fest website: https://www.sydney.edu.au/events/coding-fest
• Coding Fest Twitter: https://twitter.com/codingfest_syd

@misc{
      title={Auslan-Daily: Australian Sign Language Translation for Daily Communication and News}, 
      author={Xin Shen, Shaozu Yuan, Hongwei Sheng, Heming Du, Xin Yu},
      year={2023}
}