🧠 Shared Tasks @ WSLP 2026 – Sign Language
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🧾 Call for Shared Tasks
WSLP 2026: Workshop on Sign Language Translation
- 📍 Co-located with EMNLP 2026
- 📅 Date: TBD
- 📍 EMNLP 2026
WSLP 2026 invites participants to three Shared Tasks addressing key challenges in Indian Sign Language (ISL) processing.
🔍 Shared Tasks Overview
| Tasks | Focus | Public Dataset | Task dataset | Codabench |
|---|---|---|---|---|
| Sign Language Translation (SLT) | Sentence-level translation from ISL videos/pose to English | iSign | Translation Dataset | Translation Codabench |
| Isolated Sign Language Recognition (ISLR) | Isolated sign recognition at the word level | CISLR | Recognition Dataset | Recognition Codabench |
| Word\Sign Presence Prediction | Detecting presence of a word in a signed sentence | Word\Sign Presence Dataset | Word\Sign Presence Prediction Dataset | Word\Sign Presence Prediction Codabench |
Note: To access the public dataset, participants need to create a Hugging Face account and request access to the dataset.
📋 Shared Tasks Details
🌐 Task 1: Sign Language Translation (SLT)
Goal: Translate sentence-level Indian Sign Language (ISL) videos/poses into English text.
- Challenges: Visual-linguistic grounding, grammar, gesture ambiguity
- Use Cases: Sign-enabled chatbots, video interpreters, accessible interfaces
- Dataset: Public Dataset iSign (118,000 video-sentence pairs) , Task validation and Test dataset Translation Dataset
- Metrics: BLEU, ROUGE, chrF
- Input ➝ Output: ISL video/pose ➝ English sentence
English Translation: “The ban would mean she can’t compete in any national or other domestic events”
✋ Task 2: Isolated Sign Language Recognition (ISLR)
Goal: Recognize isolated ISL signs (words or glosses) from short video clips.
- Challenges: Sign variability, subtle motion, similar gestures
- Use Cases: Dictionary building, lookup tools, annotation
- Dataset: Dataset Recognition Dataset
- Metrics: Accuracy, Top-K Accuracy
- Input ➝ Output: Video clip ➝ Word label
Label: “National”
🔍 Task 3: Word\Sign Presence Prediction
Goal: Predict if a given word\Sign is present in a full ISL sentence video.
- Challenges: Sign spotting, context alignment
- Use Cases: Query-based video retrieval, sign search
- Dataset: Word\Sign Presence Dataset
- Metrics: Accuracy, Precision, Recall, F1
- Input ➝ Output: (Video, Word) ➝ Present / Not Present
Query Word/Sign: “National”
Sentence Video: “The ban would mean she can’t compete in any national or other domestic events” contains: “National”
🗓 Key Dates
| Event | Date |
|---|---|
| 🟢 Start Date | June 8th, 2026 |
| 📚 Training Phase | June 8th – 31st July, 2026 |
| 🧪 Testing Phase | August 1st – August 10th, 2026 |
| 📄 Paper Submission Deadline | August 20th, 2026 |
| 📬 Notification of Acceptance | August 30th, 2026 |
| 📸 Camera-ready Papers Due | September 10th, 2026 |
| 📚 Proceedings Due | September 25th, 2026 |
👥 Call for Participation
We invite researchers, students, and developers in computer vision, natural language processing, speech and gesture technology, or related fields to participate. Contribute to building inclusive tools for millions of ISL users.
📦 Submission Guidelines
- Platform: Codabench
- Team Size: Max 4 members (TBD)
- Format: To be released with dataset
- Requirements: Output on test set + short documentation
- Paper Submission: Full (8 pages) or short (4 pages) papers, following ACL Style. Double-blind review. Accepted papers get +1 page for revisions.
Contact Organizers:
- Sanjeet Singh: sanjeet@cse.iitk.ac.in
- Abhinav Joshi: ajoshi@cse.iitk.ac.in
- Tomáš Železný: zeleznyt@fav.zcu.cz
✅ Get ready to build impactful AI tools for the Deaf community.