| --- |
| pretty_name: SignQA-2026 |
| language: |
| - zh |
| - de |
| task_categories: |
| - question-answering |
| tags: |
| - sign-language |
| - video-question-answering |
| - csl-daily |
| - phoenix-2014t |
| configs: |
| - config_name: csl-daily-qa |
| data_files: |
| - split: train |
| path: CSL-daily-QA/annatation/csl_train_qa.jsonl |
| - split: validation |
| path: CSL-daily-QA/annatation/csl_dev_qa.jsonl |
| - split: test |
| path: CSL-daily-QA/annatation/csl_test_qa.jsonl |
| - config_name: phoenix14t-qa |
| data_files: |
| - split: train |
| path: Phoenix14T-QA/annatation/phoenix_train_qa.jsonl |
| - split: validation |
| path: Phoenix14T-QA/annatation/phoenix_dev_qa.jsonl |
| - split: test |
| path: Phoenix14T-QA/annatation/phoenix_test_qa.jsonl |
| --- |
| |
| # SignQA-2026 |
|
|
| SignQA-2026 is a multilingual question-answering dataset built from sign-language |
| sequence annotations. It contains Chinese QA pairs derived from CSL-Daily and |
| German QA pairs derived from PHOENIX-2014T. |
|
|
| The current release contains **annotations only**. Each record refers to a source |
| video by `video_id`; video files are not included. |
|
|
| ## Dataset configurations |
|
|
| | Configuration | Language | Train | Validation | Test | Total | |
| |---|---:|---:|---:|---:|---:| |
| | `csl-daily-qa` | Chinese (`zh`) | 92,000 | 5,385 | 5,880 | 103,265 | |
| | `phoenix14t-qa` | German (`de`) | 35,480 | 2,595 | 3,210 | 41,285 | |
| | **All** | — | **127,480** | **7,980** | **9,090** | **144,550** | |
|
|
| The dataset contains 28,910 unique video IDs. Each video ID has five QA records, |
| one for each module from M1 to M5. |
|
|
| ## Data format |
|
|
| Every JSONL row contains the following fields: |
|
|
| | Field | Type | Description | |
| |---|---|---| |
| | `video_id` | string | Identifier of the corresponding source video | |
| | `split` | string | Original split name: `train`, `dev`, or `test` | |
| | `dataset` | string | Source dataset identifier: `csl` or `phoenix` | |
| | `module` | string | QA module, from `M1` through `M5` | |
| | `pattern_id` | integer | Identifier of the question-generation pattern | |
| | `question` | string | Natural-language question | |
| | `answer` | string | Natural-language answer | |
| | `lang` | string | ISO language code: `zh` or `de` | |
|
|
| Example: |
|
|
| ```json |
| { |
| "video_id": "11August_2010_Wednesday_tagesschau-1", |
| "split": "train", |
| "dataset": "phoenix", |
| "module": "M1", |
| "pattern_id": 3, |
| "question": "Kannst du mir sagen, welches Zeichen bei Schritt 4 steht?", |
| "answer": "Das 4. Gloss lautet \"DONNERSTAG\".", |
| "lang": "de" |
| } |
| ``` |
|
|
| ## Intended use |
|
|
| SignQA-2026 is intended for research on sign-language understanding, |
| sequence-grounded question answering, multilingual QA, and evaluation of models |
| that reason over sign-language gloss sequences. |
|
|
| Users who need visual inputs must obtain the corresponding CSL-Daily and |
| PHOENIX-2014T videos separately and follow the original datasets' access terms. |
|
|
| ## Citation |
|
|
| If you use SignQA-2026 in your research, please cite our |
| [paper](https://arxiv.org/abs/2607.27826): |
|
|
| > Shiwei Gan, Lichen Wang, Xiao Liu, Yafeng Yin, Kuizhuang Liu, Sanglu Lu, |
| > and Lei Xie. *Sign Language Question Answering: A New Task, Benchmark, and |
| > Baseline for Sign Language Understanding*. 2026. |
|
|
| ```bibtex |
| @misc{gan2026signqa, |
| title = {Sign Language Question Answering: A New Task, Benchmark, and |
| Baseline for Sign Language Understanding}, |
| author = {Gan, Shiwei and Wang, Lichen and Liu, Xiao and Yin, Yafeng and |
| Liu, Kuizhuang and Lu, Sanglu and Xie, Lei}, |
| year = {2026}, |
| eprint = {2607.27826}, |
| archivePrefix = {arXiv}, |
| primaryClass = {cs.AI}, |
| doi = {10.48550/arXiv.2607.27826}, |
| url = {https://arxiv.org/abs/2607.27826} |
| } |
| ``` |
|
|
| arXiv: [2607.27826](https://arxiv.org/abs/2607.27826) [cs.AI] |
|
|
| ## Limitations |
|
|
| - This repository does not include source videos or gloss sequences. |
| - Questions and answers are tied to source-dataset video identifiers. |
| - Template-based QA patterns may not reflect the full diversity of naturally |
| occurring questions. |
| - Performance across Chinese and German should not be compared without |
| accounting for differences between the source datasets. |
|
|
| ## Licensing and attribution |
|
|
| This dataset is derived from CSL-Daily and PHOENIX-2014T. Users are responsible |
| for reviewing and complying with the licenses and terms of the original |
| datasets. The annotation license should be stated explicitly before public |
| release if it differs from the source-dataset terms. |
|
|
