Upload README.md with huggingface_hub

README.md

@@ -1,105 +1,186 @@
 ---
-dataset_info:
-  features:
-  - name: utterance_id
-    dtype: string
-  - name: session
-    dtype: int64
-  - name: dialog_id
-    dtype: string
-  - name: script_type
-    dtype: string
-  - name: speaker_id
-    dtype: string
-  - name: speaker_gender
-    dtype: string
-  - name: marker_actor_gender
-    dtype: string
-  - name: transcript
-    dtype: string
-  - name: start_time
-    dtype: float64
-  - name: end_time
-    dtype: float64
-  - name: duration
-    dtype: float64
-  - name: emotion
-    dtype: string
-  - name: emotion_full
-    dtype: string
-  - name: emotion_4class
-    dtype: string
-  - name: valence
-    dtype: float64
-  - name: activation
-    dtype: float64
-  - name: dominance
-    dtype: float64
-  - name: n_annotators_categorical
-    dtype: int64
-  - name: n_annotators_attribute
-    dtype: int64
-  - name: emotion_votes
-    dtype: string
-  - name: majority_votes
-    dtype: int64
-  - name: agreement_ratio
-    dtype: float64
-  - name: unanimous
-    dtype: bool
-  - name: has_majority
-    dtype: bool
-  - name: annotators_categorical
-    dtype: string
-  - name: annotators_categorical_comments
-    dtype: string
-  - name: annotators_attribute
-    dtype: string
-  - name: annotators_attribute_comments
-    dtype: string
-  - name: self_categorical
-    dtype: string
-  - name: self_attribute
-    dtype: string
-  - name: valence_std
-    dtype: float64
-  - name: activation_std
-    dtype: float64
-  - name: dominance_std
-    dtype: float64
-  - name: audio
-    dtype:
-      audio:
-        sampling_rate: 16000
-  splits:
-  - name: session1
-    num_bytes: 265905639.284
-    num_examples: 1819
-  - name: session2
-    num_bytes: 264644408.876
-    num_examples: 1811
-  - name: session3
-    num_bytes: 300155224.728
-    num_examples: 2136
-  - name: session4
-    num_bytes: 292025357.478
-    num_examples: 2103
-  - name: session5
-    num_bytes: 303536228.18
-    num_examples: 2170
-  download_size: 1406686600
-  dataset_size: 1426266858.546
+pretty_name: IEMOCAP (full release)
+language:
+  - en
+license: other
+license_name: usc-sail-iemocap-academic-license
+license_link: https://sail.usc.edu/iemocap/iemocap_release.htm
+tags:
+  - speech-emotion-recognition
+  - emotion
+  - valence-arousal-dominance
+  - dyadic-conversation
+  - audio
+task_categories:
+  - audio-classification
+  - automatic-speech-recognition
+size_categories:
+  - 10K<n<100K
 configs:
-- config_name: default
-  data_files:
-  - split: session1
-    path: data/session1-*
-  - split: session2
-    path: data/session2-*
-  - split: session3
-    path: data/session3-*
-  - split: session4
-    path: data/session4-*
-  - split: session5
-    path: data/session5-*
+  - config_name: default
+    data_files:
+      - split: session1
+        path: data/session1-*
+      - split: session2
+        path: data/session2-*
+      - split: session3
+        path: data/session3-*
+      - split: session4
+        path: data/session4-*
+      - split: session5
+        path: data/session5-*
 ---
+
+# IEMOCAP — full release, utterance level
+
+All 10,039 segmented utterances of the USC-SAIL **IEMOCAP** corpus with 16 kHz audio,
+transcripts, consensus emotion labels, consensus VAD ratings, per-annotator raw labels,
+and annotator-agreement statistics.
+
+**This is a private mirror.** IEMOCAP is distributed under the USC SAIL academic license,
+which requires an individually signed agreement and does not permit redistribution.
+Do not make this repository public. Anyone needing the data should obtain it from
+[sail.usc.edu/iemocap](https://sail.usc.edu/iemocap/iemocap_release.htm).
+
+## Loading
+
+```python
+from datasets import load_dataset, concatenate_datasets
+
+ds = load_dataset("cairocode/iemocap")          # 5 splits, one per session
+ds["session1"][0]["audio"]                      # {'array': ..., 'sampling_rate': 16000}
+
+# Leave-one-session-out: hold out session 5
+train = concatenate_datasets([ds[f"session{i}"] for i in (1, 2, 3, 4)])
+test = ds["session5"]
+
+# Standard 4-class benchmark subset (5,531 utterances)
+four = train.filter(lambda r: r["emotion_4class"] is not None)
+```
+
+Splits are the five recording sessions, each with a disjoint pair of actors, so
+session-wise splitting is automatically speaker-independent. Concatenate all five for
+the full corpus.
+
+## Fields
+
+### Identification
+| Field | Type | Description |
+|---|---|---|
+| `utterance_id` | str | e.g. `Ses01F_impro01_F000` |
+| `session` | int | Recording session, 1–5 |
+| `dialog_id` | str | Parent dialogue, e.g. `Ses01F_impro01` |
+| `script_type` | str | `improvisation` (4,784) or `script` (5,255) |
+| `speaker_id` | str | One of 10 actors, e.g. `Ses01F` |
+| `speaker_gender` | str | `female` (4,800) / `male` (5,239) |
+| `marker_actor_gender` | str | Which actor wore the MoCap markers in this dialogue |
+| `start_time`, `end_time`, `duration` | float | Seconds, relative to the parent dialogue |
+
+### Audio and text
+| Field | Type | Description |
+|---|---|---|
+| `audio` | Audio | 16 kHz mono, PCM-16, embedded. Native rate — nothing was resampled |
+| `transcript` | str | Manual transcription. Present for all 10,039 rows |
+
+### Consensus labels
+| Field | Type | Description |
+|---|---|---|
+| `emotion` | str | Majority-vote code, or `xxx` when no majority exists |
+| `emotion_full` | str | Same, spelled out (`undecided` for `xxx`) |
+| `emotion_4class` | str \| None | `angry` / `happy` / `neutral` / `sad`, with `exc` merged into `happy`. `None` for the other 4,508 rows |
+| `valence`, `activation`, `dominance` | float | Corpus-provided mean over the external dimensional annotators, on a 1–5 scale. Self-evaluations are excluded, per the corpus README |
+
+`emotion` is the corpus's own ground-truth field, not recomputed here.
+
+### Agreement
+| Field | Type | Description |
+|---|---|---|
+| `n_annotators_categorical` | int | Always 3 external annotators |
+| `n_annotators_attribute` | int | Dimensional annotators: 2 (8,666), 3 (1,279), 4 (58), 1 (36) |
+| `emotion_votes` | JSON str | Category → vote count, e.g. `{"fru": 2, "neu": 1}` |
+| `majority_votes` | int | Votes for the most-chosen category |
+| `agreement_ratio` | float | `majority_votes / 3`. Corpus mean **0.673** |
+| `unanimous` | bool | All 3 annotators gave the same primary label (2,132 rows, 21.2%) |
+| `has_majority` | bool | `emotion != "xxx"` (7,532 rows, 75.0%) |
+| `valence_std`, `activation_std`, `dominance_std` | float | Sample standard deviation across external dimensional annotators |
+
+Annotators could assign **more than one** category to an utterance, so vote counts in
+`emotion_votes` may sum to more than 3. `agreement_ratio` and `unanimous` are computed
+over each annotator's *first* (primary) label.
+
+Corpus-level **Fleiss' κ = 0.276** on primary labels (3 raters, 10 categories, N = 10,039)
+— low, which is characteristic of the corpus and the reason a quarter of utterances have
+no majority label.
+
+### Per-annotator raw labels
+| Field | Type | Description |
+|---|---|---|
+| `annotators_categorical` | JSON str | `{"E2": ["neu"], "E3": ["neu"], "E4": ["neu", "ang"]}` |
+| `annotators_attribute` | JSON str | `{"E3": [3, 2, 2], "E4": [2, 3, 3]}` — `[valence, activation, dominance]`, 1–5 |
+| `annotators_categorical_comments` | JSON str | Free-text annotator notes, where given |
+| `annotators_attribute_comments` | JSON str | As above, for dimensional ratings |
+| `self_categorical` | JSON str \| None | The performing actor's own categorical rating |
+| `self_attribute` | JSON str \| None | The actor's own `[val, act, dom]` |
+
+Annotator codes are the corpus's own (`E1`–`E6` external; `F*`/`M*` the actors themselves).
+These are *not* stable identities across sessions: `E2` in session 1 is not necessarily
+`E2` in session 3. Do not model annotator identity across sessions.
+
+Self-evaluations cover only **2,409 of 10,039** utterances, and **session 4 has none at
+all** — these columns are `None` elsewhere. They are excluded from the consensus VAD.
+
+JSON-encoded columns are strings; `json.loads` them.
+
+## Label distribution
+
+| Code | Emotion | Count | Share |
+|---|---|---|---|
+| `xxx` | undecided | 2,507 | 25.0% |
+| `fru` | frustrated | 1,849 | 18.4% |
+| `neu` | neutral | 1,708 | 17.0% |
+| `ang` | angry | 1,103 | 11.0% |
+| `sad` | sad | 1,084 | 10.8% |
+| `exc` | excited | 1,041 | 10.4% |
+| `hap` | happy | 595 | 5.9% |
+| `sur` | surprised | 107 | 1.1% |
+| `fea` | fearful | 40 | 0.4% |
+| `oth` | other | 3 | 0.0% |
+| `dis` | disgusted | 2 | 0.0% |
+
+4-class subset: neutral 1,708 · happy 1,636 (595 `hap` + 1,041 `exc`) · angry 1,103 · sad 1,084 = **5,531**.
+
+Rows per session: 1,819 / 1,811 / 2,136 / 2,103 / 2,170. Total speech: **12.44 hours**.
+
+## Provenance
+
+Built from `IEMOCAP_full_release` by parsing the aggregate
+`SessionX/dialog/EmoEvaluation/*.txt` files (151 dialogues), joined to
+`SessionX/dialog/transcriptions/` and `SessionX/sentences/wav/`. Every utterance matched a
+wav file and a transcript; no rows were dropped or imputed.
+
+The aggregate `EmoEvaluation` files are the authoritative source. The
+`EmoEvaluation/Categorical/`, `Attribute/` and `Self-evaluation/` subdirectories duplicate
+the same annotations but encode the numeric scales on an inconsistent polarity — the same
+annotator, utterance and free-text comment appears there with different numbers. Those
+subdirectories were deliberately **not** used.
+
+### Not included
+Dialogue-level audio and video, MoCap (face, head, hand), forced alignments
+(`ForcedAlignment/*.wdseg|phseg|syseg`), and the `.anvil` annotation sources. All remain in
+the local `IEMOCAP_full_release` tree and can be added on request.
+
+## Citation
+
+Any published work using IEMOCAP must cite:
+
+```bibtex
+@article{busso2008iemocap,
+  title={IEMOCAP: Interactive emotional dyadic motion capture database},
+  author={Busso, Carlos and Bulut, Murtaza and Lee, Chi-Chun and Kazemzadeh, Abe and
+          Mower, Emily and Kim, Samuel and Chang, Jeannette N. and Lee, Sungbok and
+          Narayanan, Shrikanth S.},
+  journal={Language Resources and Evaluation},
+  volume={42}, number={4}, pages={335--359}, year={2008},
+  publisher={Springer}
+}
+```