--- license: cc-by-nc-sa-4.0 language: - ms - zsm pretty_name: MySign — Malaysian Sign Language 3D Motion Capture size_categories: - 1K **Note**: this dataset is **not** loadable via `datasets.load_dataset(...)` as a tabular split, because the data itself is binary `.fbx`. `metadata.csv` is an index over the FBX files; consumers must read the file at `file_name` to access the motion data. ## Dataset Summary - **Modality**: 3D skeletal motion capture (`.fbx`) - **Language**: Malaysian Sign Language (BIM) — ISO `ms` / `zsm` - **Signers**: 5 (`Signer001` … `Signer005`) - **Sample**: one `.fbx` per `(signer, gloss, take)` - **License**: CC BY-NC-SA 4.0 - **Source repository**: ## Repository Structure ``` MySign/ ├── Signer001/ │ ├── Above.fbx │ ├── Apologize.fbx │ ├── Apologize.001.fbx │ └── ... ├── Signer002/ ├── Signer003/ ├── Signer004/ ├── Signer005/ ├── metadata.csv # index over all .fbx files ├── croissant.json # Croissant 1.0 ML-dataset metadata (JSON-LD) ├── README.md └── .gitattributes ``` ## `metadata.csv` Schema `metadata.csv` is a UTF-8 CSV with a header row. **Each row corresponds to exactly one `.fbx` file in the repository.** | Column | Type | Description | |-------------|---------|-------------| | `file_name` | string | Repository-relative path to the `.fbx`, e.g. `Signer001/Above.fbx`. | | `gloss` | string | Normalized gloss label (UPPERCASE). See [Gloss Normalization](#gloss-normalization). | | `signer_id` | string | One of `Signer001` … `Signer005`. | | `take` | integer | Take number for the `(signer_id, gloss)` pair. The original recording is `1`; Blender-style duplicate suffixes `.001`, `.002` map to takes `2`, `3`. | ### Example rows ```csv file_name,gloss,signer_id,take Signer001/Above.fbx,ABOVE,Signer001,1 Signer001/Apologize.fbx,APOLOGIZE,Signer001,1 Signer001/Apologize.001.fbx,APOLOGIZE,Signer001,2 Signer002/Actor,_Actress.fbx,ACTOR / ACTRESS,Signer002,1 Signer003/1-hr.fbx,1 HOUR,Signer003,1 Signer004/Less (I).fbx,LESS(I),Signer004,1 ``` > **Path quoting**: some `file_name` values contain commas (e.g. `Signer002/Actor,_Actress.fbx`). The CSV is written with Python's default `csv.writer`, which quotes such fields automatically. Read it with any standard CSV parser (pandas, `csv.DictReader`). ### Gloss Normalization The `gloss` column is derived from each filename and normalized so that the same sign performed by different signers gets the same label. The normalization, applied by `generate_metadata_remote.py`, is: 1. Strip Blender suffix `.001` / `.002` (recorded into `take`). 2. Replace `_` and `-` with spaces. 3. Treat `,` and `;` as synonym separators, joined as `WORD_A / WORD_B`. 4. Uppercase. 5. Expand time-unit abbreviations: `HR→HOUR`, `MIN→MINUTE`, `MTH→MONTH`, `WK→WEEK`, `YR→YEAR`, `SEC→SECOND` (and plurals). 6. Normalize whitespace around parentheses: `WORD (X)` → `WORD(X)`. 7. Strip unbalanced trailing `)`. 8. Plural→singular merge: when the corpus contains both forms of a word (e.g. `COURSES` and `COURSE`), the plural is rewritten to the singular. A small block-list keeps semantically distinct plurals (`NEWS`, `SHORTS`, `MATHEMATICS`) as plurals. 9. A small hand-curated override map (currently: `COCHLEAR / IMPLANT` → `COCHLEAR IMPLANT`) fixes cases that no general rule can fix safely. A full audit of the plural→singular merges is printed by the script every time it runs; check that list before publishing. ## `.fbx` Files - Format: Autodesk Filmbox (binary `.fbx`). - One file per take. - The `file_name` column of `metadata.csv` is the canonical pointer to each file. The same path can be resolved as `https://huggingface.co/datasets/mysigner/MySign/resolve/main/`. ## Croissant Metadata A Croissant 1.0 (JSON-LD) description is provided as `croissant.json`. It declares: - The repository as a `cr:FileObject` (`encodingFormat: git+https`). - `metadata.csv` as a `cr:FileObject` of type `text/csv`. - All `Signer*/*.fbx` files as a `cr:FileSet` named `fbx-files` (`encodingFormat: model/vnd.fbx`). - A `cr:RecordSet` named `signs` exposing the four columns above. The `file_name` field carries `references: fbx-files`, which tells Croissant consumers the value is a path into the FBX FileSet. **Limitation**: Croissant 1.0 has no native semantics for FBX. `mlcroissant` will treat every FBX as an opaque binary resource — it will not parse skeletons, animation curves, or any FBX-internal structure. Consumers must use a real FBX library (e.g. Autodesk FBX SDK, Blender, [`pyfbx`](https://pypi.org/project/pyfbx/)) to read the motion data. ## Usage ### List records via `metadata.csv` ```python import pandas as pd df = pd.read_csv( "https://huggingface.co/datasets/mysigner/MySign/resolve/main/metadata.csv" ) print(df.head()) print(df["signer_id"].value_counts().sort_index()) print(df["gloss"].nunique(), "unique glosses") ``` ### Download a specific FBX ```python from huggingface_hub import hf_hub_download local_path = hf_hub_download( repo_id="mysigner/MySign", filename="Signer001/Above.fbx", repo_type="dataset", ) print(local_path) # local cache path; open with your FBX library ``` ### Inspect via Croissant (mlcroissant) ```python import mlcroissant as mlc ds = mlc.Dataset( "https://huggingface.co/datasets/mysigner/MySign/resolve/main/croissant.json" ) print(ds.metadata.name, "—", ds.metadata.description[:80]) for i, rec in enumerate(ds.records(record_set="signs")): print(rec) if i >= 4: break ``` `ds.records("signs")` yields one Python dict per `.fbx`, with `file_name`, `gloss`, `signer_id`, `take`. The FBX bytes are not auto-loaded — read them yourself from `file_name`. ## License This dataset is released under [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/). You may share and adapt the work for non-commercial purposes, provided you give appropriate credit and distribute derivative works under the same license. ## Citation ```bibtex @misc{mysign2026, title = {MySign: A High-Fidelity Motion-Capture Dataset for 3D Sign Generation in Bahasa Isyarat Malaysia}, author = {{mysigner}}, year = {2026}, howpublished = {Hugging Face Datasets}, url = {https://huggingface.co/datasets/mysigner/MySign}, note = {CC BY-NC-SA 4.0} } ``` (Replace with the canonical citation when a paper or technical report becomes available.) ## Limitations - **Not auto-loadable**: Hugging Face's Dataset Viewer cannot render `.fbx`. The Viewer will not work for this dataset, and `datasets.load_dataset("mysigner/MySign")` will not produce a usable split. Use the workflows above instead. - **Gloss is filename-derived**: glosses come from filenames written by signers/annotators with slightly different conventions, then normalized. Some collisions may still exist; run the script's plural-merge audit before relying on a particular gloss inventory. - **Five signers**: signer-conditioned models trained on MySign will have limited speaker coverage. - **Take semantics are best-effort**: the `take` column distinguishes Blender-duplicated files (`.001`, `.002`) from the original recording, but it does not encode whether a take was a clean recording or a retry. - **No segmentation, no transcription**: each FBX is one isolated sign. The dataset does not include continuous-signing video, glossed sentences, or non-manual annotations.