Add dataset card

README.md

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+---
+license: other
+license_name: research-use-only
+license_link: LICENSE
+language:
+- en
+task_categories:
+- video-classification
+- audio-classification
+- text-classification
+tags:
+- multimodal
+- sarcasm-detection
+- humor-detection
+- mustard
+- ur-funny
+- affective-computing
+size_categories:
+- 1K<n<10K
+---
+
+# CTM Affective Benchmarks: MUStARD + UR-FUNNY
+
+Preprocessed multimodal media and text splits for the two affective-reasoning
+benchmarks used in the `ctm-ai` `exp_affective` experiments:
+
+- **MUStARD** — multimodal sarcasm detection from TV sitcom clips
+  (*Friends*, *The Big Bang Theory*, *The Golden Girls*, *Sarcasmaholics*).
+- **UR-FUNNY** — multimodal humor detection from TED talk clips.
+
+This repo bundles the **derived media** (raw clips, muted video streams, and
+extracted audio) alongside the **JSON text splits**, so an experiment run can
+fetch everything from one place.
+
+## Repository layout
+
+```
+mustard/
+  mmsd_raw_data/utterances_final/   690 mp4  — raw clips (video + audio)
+  mustard_muted_videos/             690 mp4  — video-only (audio stream removed)
+  mustard_audios/                   356 mp4  — audio-only, test split only
+  mustard_dataset/                    9 json — test split + evaluation subsets
+  mustard_smoke3.json                        — 3-example smoke test
+
+urfunny/
+  urfunny_videos/                   992 mp4  — raw clips (video + audio)
+  urfunny_muted_videos/             992 mp4  — video-only (audio stream removed)
+  urfunny_audios/                   992 mp4  — audio-only
+  data_raw/                           5 json — test split + evaluation subsets
+  urfunny_smoke3.json                        — 3-example smoke test
+```
+
+Total: 4,728 files, ~4.55 GB.
+
+### Naming conventions
+
+- MUStARD clip ids look like `1_10004` (non-sarcastic pool) and `2_223`
+  (sarcastic pool). Audio files add an `_audio` suffix: `2_223_audio.mp4`.
+- UR-FUNNY clip ids are plain integers (`1008`), with audio also suffixed
+  `_audio` (`1008_audio.mp4`).
+- Media files carry the `.mp4` container throughout, **including the
+  audio-only tracks** — they are audio streams in an mp4 container, not video.
+
+### Coverage note
+
+`mustard_audios/` contains **356** files, not 690: audio was extracted only for
+the clips in `mustard_dataset/mustard_dataset_test.json` (the 356-example test
+split). Those 356 ids are a strict subset of the 690 ids in
+`mustard_muted_videos/` and `mmsd_raw_data/utterances_final/`. UR-FUNNY has
+full 992/992/992 coverage across all three modality folders.
+
+## Text split schemas
+
+`mustard/mustard_dataset/mustard_dataset_test.json` — a dict keyed by clip id
+(356 entries):
+
+| field | description |
+|---|---|
+| `utterance` | the target utterance text |
+| `speaker` | speaker of the target utterance |
+| `context` | list of preceding utterances |
+| `context_speakers` | speakers for each context utterance |
+| `show` | source sitcom |
+| `sarcasm` | boolean label |
+
+`urfunny/data_raw/urfunny_dataset_test.json` — a dict keyed by clip id
+(992 entries):
+
+| field | description |
+|---|---|
+| `context_sentences` | list of setup sentences |
+| `punchline_sentence` | the punchline |
+| `label` | humor label |
+
+The remaining JSON files in each folder are evaluation subsets
+(`*_subset_5/6/20/100.json`) and retry/missing-id lists used for partial reruns.
+
+## Usage
+
+```python
+from huggingface_hub import snapshot_download
+
+# everything (~4.55 GB)
+snapshot_download("lwaekfjlk/ctm-affective", repo_type="dataset")
+
+# just the MUStARD text splits
+snapshot_download(
+    "lwaekfjlk/ctm-affective",
+    repo_type="dataset",
+    allow_patterns="mustard/mustard_dataset/*",
+)
+
+# just UR-FUNNY audio
+snapshot_download(
+    "lwaekfjlk/ctm-affective",
+    repo_type="dataset",
+    allow_patterns="urfunny/urfunny_audios/*",
+)
+```
+
+There is intentionally no `configs:` block in the card metadata: the JSON files
+are id-keyed dicts rather than record lists, so the dataset viewer would not
+parse them. Load them with `json.load` directly.
+
+## Provenance and licensing
+
+The clips are **derived from third-party copyrighted footage** (TV sitcom
+episodes for MUStARD, TED talks for UR-FUNNY) and are redistributed here only
+as preprocessed research artifacts. Use is intended for non-commercial academic
+research. Rights to the underlying footage remain with their original owners;
+consult the upstream datasets for their terms before redistributing.
+
+Please cite the original datasets:
+
+```bibtex
+@inproceedings{castro2019towards,
+  title     = {Towards Multimodal Sarcasm Detection (An {\_}Obviously{\_} Perfect Paper)},
+  author    = {Castro, Santiago and Hazarika, Devamanyu and P{\'e}rez-Rosas, Ver{\'o}nica
+               and Zimmermann, Roger and Mihalcea, Rada and Poria, Soujanya},
+  booktitle = {Proceedings of the 57th Annual Meeting of the Association for
+               Computational Linguistics (ACL)},
+  year      = {2019}
+}
+
+@inproceedings{hasan2019urfunny,
+  title     = {{UR-FUNNY}: A Multimodal Language Dataset for Understanding Humor},
+  author    = {Hasan, Md Kamrul and Rahman, Wasifur and Zadeh, Amir and Zhong, Jianyuan
+               and Tanveer, Md Iftekhar and Morency, Louis-Philippe and Hoque, Mohammed (Ehsan)},
+  booktitle = {Proceedings of the 2019 Conference on Empirical Methods in Natural
+               Language Processing (EMNLP)},
+  year      = {2019}
+}
+```