Duplicate from CLERC-DATA/epee

Co-authored-by: Florian Méloux <CLERC-IO@users.noreply.huggingface.co>

BENCHMARK.md

@@ -0,0 +1,111 @@
+# Épée v0.4 · Signer-Robustness Benchmark
+
+**What it shows:** signer variation is the core problem in sign-language AI, and the fix is
+*more signers and more data*, not a bigger model. Re-measured on the eight v0.4 signers with the
+v0.2 / v0.3 protocol, **with one deliberate change: hand slots are now consistent in train and
+test.**
+
+The model is trained on release signers and tested on **two native Deaf signers with no clips in
+this release** (Signer A and Signer B, pseudonymized, from the broader CLERC corpus). They recorded
+under the same protocol and share prompts with the grid signers: same content, brand-new body,
+the controlled comparison a signer-generalization test needs. No clip is shared between train and
+test.
+
+![benchmark](benchmark.png)
+
+---
+
+## Why the v0.3 numbers are not comparable
+
+v0.1 to v0.3 shipped with crossed hand slots: the `0-20` / `21-41` blocks were not consistently
+the same hand, and the convention differed by signer (measured on the published v0.3 files: most
+decidable clips crossed). A model trained on that learns "which slot holds the active hand" as a
+signer cue, and a stranger whose slots go the other way is penalized for it. v0.4 fixes the
+release at build time and this run fixes the frozen test segments with the same rule, per sample:
+Signer A needed 10 of 1,961
+segments swapped, Signer B 1210 of
+1,453. Fixing only the test side would be an exploit, not a correction;
+both sides are fixed here.
+
+So the effects are separated, all at 8 seeds:
+
+| Training data | Signer A | Signer B |
+|---|---|---|
+| v0.3 as published (crossed slots, train and test) | 69% ± 5 | 58% ± 6 |
+| v0.3 recordings, slots fixed (same 1,199 clips) | 76% ± 4 | 60% ± 4 |
+| v0.3's six signers at 300 clips each (2,477 segments) | 77% ± 3 | 63% ± 9 |
+| all eight signers, subsampled to the same 2,477 segments | 79% ± 4 | 64% ± 6 |
+| **v0.4, eight signers, 2,400 clips (2,877 segments)** | **81% ± 1** | **69% ± 4** |
+
+The first step is the correction alone (same clips). The second is more clips for the same six
+signers. The third row holds the volume fixed and only changes the signer mix: at equal volume the difference is +2.3 points on Signer A and +1.4 on Signer B, within run-to-run spread (±4): this run does not separate diversity from volume.
+The last row adds the remaining volume.
+
+---
+
+## Setup
+
+| | |
+|---|---|
+| Model | small BiLSTM (1 layer, hidden 64, bidirectional, mean-pool → linear) |
+| Input | keypoint sequences, hands + arms (48 pts, x/y), shoulder-normalized, resampled to 24 frames |
+| Task | sign classification on the **same 24 glosses** as v0.2 and v0.3 (vocabulary frozen) |
+| Train | 2,877 gloss segments from the eight release signers (1,393 in v0.3) |
+| Test | Signer A: 1,961 segments · Signer B: 1,453 segments (same as v0.2 / v0.3) |
+| Chance | 4.2% (1 / 24) · **8 seeds** per configuration, mean ± std |
+| Metrics | top-1 accuracy **and macro-F1** |
+
+## Result 1 · More signers → better on a brand-new signer
+
+Tested on Signer A. Mean over signer combinations at each size: every single signer at k = 1, then
+a seeded sample of combinations (C(8, k) reaches 70; the sample is an unbiased estimate of the
+all-combinations mean reported in v0.2 and v0.3).
+
+| # training signers | combinations | Accuracy | Macro-F1 |
+|---|---|---|---|
+| 1 | 8 | 42% ± 15 | 0.28 |
+| 2 | 5 | 64% ± 12 | 0.52 |
+| 3 | 5 | 67% ± 6 | 0.57 |
+| 4 | 5 | 73% ± 8 | 0.65 |
+| 5 | 5 | 75% ± 7 | 0.67 |
+| 6 | 5 | 77% ± 4 | 0.69 |
+| 7 | 5 | 79% ± 5 | 0.71 |
+| 8 | 1 | 81% ± 1 | 0.74 |
+
+A signer the model *has* seen scores 83% (ceiling). At eight training signers the stranger
+gap is **1 point**. Second stranger, Signer B: 69%.
+
+The ± is the spread over seeds and combinations. At k = 8 there is a single combination, so its ±
+is seed variance only: the narrowing toward k = 8 is partly a counting effect, not only a
+stabilization of the model.
+
+## Result 2 · More data → still rising, more slowly
+
+Same held-out signer; training set grown by a clean random fraction of the v0.4 pool:
+
+| Training examples | 80 | 160 | 260 | 380 | 520 | 680 | 858 | 1,044 | 1,393 | 2,157 | 2,877 |
+|---|---|---|---|---|---|---|---|---|---|---|---|
+| Accuracy | 42% | 61% | 56% | 70% | 70% | 73% | 72% | 75% | 76% | 77% | 80% |
+
+---
+
+## Caveats
+
+- 24-gloss shared subset, frozen from v0.2 for comparability. It is a measurement instrument,
+  not a ceiling on what the release covers (1,501 unique glosses in v0.4).
+- **Dominant hand is not normalized.** Hand slots are fixed to the left / right of the body, they do
+  not swap dominant and non-dominant hands. Alone, signers range from 14% (ALPHA) to
+  62% (CHARLIE) on Signer A. The low end is ALPHA, whose dominant hand is on the opposite side
+  of the frame from Signer A's (it was already the low end in v0.3), not the own-register signers.
+  Signer B is in the opposite case to Signer A, which is consistent with its lower score. Mirroring
+  left-dominant signers is a modelling choice left to the user.
+- FOXTROT, GOLF, HOTEL cover fewer than the 24 test glosses (FOXTROT 18, GOLF 15, HOTEL 18):
+  their prompt sets are other registers (declarative sentences).
+- The full-pool point of the data curve (80%) and the headline v0.4 number (81%)
+  train on the same segments in a different order (the curve shuffles before slicing); the gap is
+  run-to-run noise, not a different setting.
+- Measures generalization across signer **bodies**, not across topics.
+- Small BiLSTM by design; the 1-signer vs many-signer gap is a data property.
+- 26 Signer A
+  and 8 Signer B
+  test segments had too little hand evidence to decide their slots and are left as extracted.

README.md

@@ -0,0 +1,479 @@
+---
+license: cc-by-nc-sa-4.0
+language:
+- ase
+- en
+tags:
+- sign-language
+- asl
+- american-sign-language
+- keypoints
+- mediapipe
+- pose-estimation
+- multimodal
+- accessibility
+- deaf
+- benchmark
+pretty_name: "CLERC Épée v0.4 - Sign Language Data Layer"
+size_categories:
+- 1K<n<10K
+task_categories:
+- feature-extraction
+- translation
+- token-classification
+---
+
+# CLERC Épée v0.4
+
+**The first AI-grade sign language data layer.**
+
+![clips](https://img.shields.io/badge/clips-2,400-10b981) ![duration](https://img.shields.io/badge/signed_duration-179.93_min-10b981) ![signers](https://img.shields.io/badge/Deaf_signers-8-10b981) ![phrases](https://img.shields.io/badge/parallel_grid-302_phrases_×_5_signers-0ea5e9) ![keypoints](https://img.shields.io/badge/keypoints-128_per_frame-0ea5e9) ![license](https://img.shields.io/badge/license-CC_BY--NC--SA_4.0-64748b)
+
+> **CLERC** builds the data infrastructure layer for sign language in multimodal AI.
+> 🌐 [clerc.io](https://clerc.io) · 💻 [Toolkit on GitHub](https://github.com/melouxflorian-jpg/epee-asl-toolkit) · ✉️ [florian@clerc.io](mailto:florian@clerc.io)
+> Commercial licensing and full corpus access on request.
+
+The corpus is built around one idea: **the same phrase, signed by several Deaf signers, in a controlled recording protocol.** This is what that looks like, straight from the release keypoints:
+
+![One phrase, five signers](assets/hero_parallel.gif)
+
+Every clip in the parallel grid has this property. Inter-signer variation - style, rhythm, signing space, handshape choices - stops being noise you fight and becomes the thing you can measure.
+
+**v0.4 doubles the corpus to 2,400 clips and the signer pool from 6 to 8**, widens the parallel grid from 201 to 302 phrases, adds two new signers on their own registers, and **fixes the hand slots of every earlier release** (see [the correction note](#correction-note-hand-slots)).
+
+> CLERC builds the data layer underneath sign language AI - not a translation tool, not an accessibility app. Infrastructure.
+
+## Quick start
+
+```python
+import json, numpy as np, pandas as pd
+from pathlib import Path
+from huggingface_hub import snapshot_download
+
+ROOT = Path(snapshot_download(repo_id="CLERC-DATA/epee", repo_type="dataset"))
+meta = pd.read_csv(ROOT / "metadata.csv")
+
+# five renderings of the same phrase, ready to compare
+grid = meta[meta.parallel == "yes"]
+phrase = grid[grid.phrase_id == 2]
+clips = {r.signer_id: np.load(ROOT / "keypoints" / f"{r.clip_id}.npy")
+         for r in phrase.itertuples()}          # each (n_frames, 128, 3)
+```
+
+Or in five minutes with the open Python toolkit: [`epee-asl-toolkit`](https://github.com/melouxflorian-jpg/epee-asl-toolkit) - loaders, keypoint visualization, inter-signer variability analysis.
+
+---
+
+## Dataset Summary
+
+- **2,400 ASL clips, 179.93 minutes of continuous signing** - 8 Deaf signers, 300 clips each
+- **Parallel grid** - 302 phrases signed by 5 of the 8 signers (1,500 clips), for direct inter-signer variability analysis
+- **Three more registers** - FOXTROT, GOLF and HOTEL each contribute 300 sentences from their own prompt sets, disjoint from the grid and from each other, so the corpus is not only short conversational phrases
+- **Hand slots verified per clip** - `0-20` is the hand at the signer's left wrist, `21-41` at the right wrist, checked against the pose on every clip of the built release
+- **Explicit phrase alignment** - a `phrase_id` column pairs renderings of the same phrase across signers, no id arithmetic required
+- **Multimodal keypoints** - hands, body, eyes, mouth, head silhouette (MediaPipe-extracted)
+- **Linguistically validated** - ASL gloss annotations with temporal segmentation
+
+> **This release ships extracted keypoints and annotations only - no raw video.** Source clips remain proprietary; access is reserved for commercial licensing (contact **florian@clerc.io**).
+
+This is **v0.4**, a pilot release representing a portion of the full CLERC catalog. Full corpus access available via commercial license.
+
+---
+
+## Benchmark - why multi-signer data matters
+
+A small BiLSTM trained on the release signers and tested on signers held **entirely outside** the
+training set shows the core result: **one signer does not generalize to a stranger, more signers do.**
+
+![benchmark](benchmark.png)
+
+- Train on 1 → … → 8 signers, tested on a brand-new signer: **42% → 64% → 67% → 73% → 75% → 77% → 79% → 81%** accuracy (macro-F1 0.28 → 0.74).
+- More data still lifts it: **42% → 80%** as training examples grow (2,877 segments in the v0.4 pool, 1,393 in v0.3).
+- Second stranger, same protocol: **69%** on the full v0.4 pool.
+- Tested on two signers with **no clips in this release**, same 24-gloss subset, same test segments and same 8 seeds as the v0.2 and v0.3 measurements.
+
+**These numbers are not comparable to the v0.3 card as published**, because v0.3 was trained and
+tested with crossed hand slots. To keep the comparison honest the run separates the two effects on
+the stranger signer: the v0.3 recordings scored **69%** as published, **76%**
+once their hand slots are fixed (correction alone, same clips), and the full v0.4 pool reaches
+**81%**.
+
+Full method, numbers, and honest caveats: **[BENCHMARK.md](BENCHMARK.md)**.
+
+---
+
+## Dataset Statistics
+
+| Metric | Value |
+|---|---|
+| Total clips | 2,400 (300 per signer) |
+| Signers | 8 (ALPHA, BRAVO, CHARLIE, DELTA, ECHO, FOXTROT, GOLF, HOTEL) |
+| Parallel grid | 1,500 clips over 302 phrases (5 signers) |
+| Own registers | 900 clips, 900 phrases (FOXTROT, GOLF, HOTEL, 300 each, disjoint prompt sets) |
+| Unique phrases | 1,202 |
+| Total frames | 323,872 |
+| Mean clip length | 135 frames (≈ 4.5 s @ 30 fps) |
+| Total signed duration | 179.93 min |
+| Gloss tokens | 10,441 |
+| Unique glosses | 1,501 |
+| Mean segments per clip | 4.35 |
+| MediaPipe head-silhouette detection | 99.98% of frames |
+| Hand slots verified against the pose | 99.8% of clips (5 undecidable, flagged) |
+| Frame rate | 29.9 – 30.1 fps |
+| Coordinate space | MediaPipe image-normalized (signer perspective) |
+
+**Top 10 glosses** (cumulative coverage of corpus):
+
+| # | Gloss | Tokens | % of corpus |
+|---|---|---|---|
+| 1 | YOU | 629 | 6.0% |
+| 2 | QUESTION | 576 | 5.5% |
+| 3 | YOUR | 386 | 3.7% |
+| 4 | I | 275 | 2.6% |
+| 5 | WHAT | 263 | 2.5% |
+| 6 | MY | 193 | 1.8% |
+| 7 | HAVE | 124 | 1.2% |
+| 8 | TIME | 115 | 1.1% |
+| 9 | NAME | 112 | 1.1% |
+| 10 | WHERE | 106 | 1.0% |
+
+---
+
+## Languages
+
+- American Sign Language (ASL) - ISO 639-3: `ase`
+- Written translations in English
+
+---
+
+## Dataset Structure
+
+```
+epee/
+├── keypoints/           # 2,400 .npy arrays, shape (n_frames, 128, 3)
+├── annotations/         # 2,400 .json files
+└── metadata.csv         # master index (1 row per clip)
+```
+
+### Keypoint layout (128 landmarks per frame)
+
+| Indices | Region | Source | Notes |
+|---------|--------|--------|-------|
+| 0–20 | Left hand (21 points) | MediaPipe Hands | hand at the signer's left wrist (Pose 15), verified per clip |
+| 21–41 | Right hand (21 points) | MediaPipe Hands | hand at the signer's right wrist (Pose 16), verified per clip |
+| 42–53 | Upper body (12 points) | MediaPipe Pose [11:23] | shoulders, elbows, wrists, finger anchors |
+| 54–63 | Lower body (10 points) | MediaPipe Pose [23:33] | hips, knees, ankles, heels, feet - spatial context, optional |
+| 64–91 | Eyes + mouth only (28 points) | MediaPipe Face | privacy-preserving subset |
+| 92–127 | Head silhouette (36 points) | MediaPipe FaceMesh `FACE_OVAL` | forehead, jaw, ears - outline only, no internal features |
+
+The 36 head-silhouette landmarks come from MediaPipe FaceMesh `FACE_OVAL` indices `10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288, 397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136, 172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109` (in that traversal order). The points form a closed polygon outlining the head - no internal facial features are included, so the privacy stance is preserved.
+
+### Coordinate space
+
+Coordinates are MediaPipe's **image-normalized space**, NOT clipped to `[0, 1]`:
+
+- **x** is in `[0, 1]` (frame width); a landmark extrapolated just off-frame can fall slightly outside `[0, 1]`
+- **y** is in `[0, 1]` for points visible in frame, but can exceed `1.0` for body landmarks extrapolated below the visible frame
+- **z** is depth relative to the hips, roughly in MediaPipe Pose's world-scale units
+
+Source clips are framed waist-up. Lower-body landmarks (dataset indices **54–63**) come from MediaPipe Pose's full-body prediction. For hand/face-only SLR pipelines, they can be dropped:
+
+```python
+kp_slr = np.concatenate([kp[:, :54], kp[:, 64:]], axis=1)  # → (n_frames, 118, 3)
+```
+
+Zero values `(0, 0, 0)` indicate a landmark was not detected for that frame (e.g. an off-screen hand).
+
+### Correction note: hand slots
+
+**v0.1, v0.2 and v0.3 shipped with crossed hand slots.** In those releases the `0-20` / `21-41`
+blocks were not consistently the same hand: measured on the published v0.3 files, **61.7%
+of the clips whose convention can be decided had the two hands swapped**, and the rate differed by
+signer. The swap correction existed in the build but a bug kept it from firing, and nothing checked
+the built files.
+
+In v0.4 every clip is re-anchored at build time (hand root compared to the Pose wrists, majority over
+all frames where a hand is visible), and the **built files are re-checked independently** before
+release: 0 crossed out of 2,395 decidable clips (0.00%). The `hand_slots` column says `verified` for every clip whose convention
+was decided, `unverified` for the 5 clips with too little hand evidence to decide;
+those are left as extracted.
+
+If you trained on v0.1 to v0.3, re-download: a model that learned on mixed slots learns signer
+identity as a shortcut and under-performs on new signers. Earlier versions stay reachable under their
+tags for reproducibility, with the defect.
+
+### Gloss conventions
+
+Glosses (uppercase ASL labels) follow a few conventions worth knowing before training:
+
+**Base gloss** - `WHAT`, `YOU`, `BATHROOM`. The standard form of a sign.
+
+**Variants - `BASE_N`** (e.g. `SIGN_2`, `WHAT_3`). Alternative ways to sign the same English concept (different handshape, location, or movement). The number `N` is an internal disambiguator, not an intensity marker. Treat `WHAT`, `WHAT_2`, `WHAT_3` as siblings sharing the same English target.
+
+**Directional / movement suffixes** - `POINTER_RIGHT`, `GO_LEFT`, `HOW_RIGHT_MOVE`. These mark spatial/movement components inherent to the sign and should not be collapsed with their base form.
+
+**Phrase repetitions** - Some clips contain the target phrase signed more than once (emphasis, demonstration, self-correction). Each occurrence is a separate gloss segment. This is natural signer behavior, not a labeling error.
+
+**Recommended preprocessing**
+
+```python
+import re
+def base_gloss(g):
+    return re.sub(r"_\d+$", "", g)   # SIGN_2 → SIGN
+
+from collections import Counter
+def has_repeat(segments):
+    return any(c >= 2 for c in Counter(s["gloss"] for s in segments).values())
+```
+
+### Annotation schema (per clip)
+
+```json
+{
+  "clip_id": "clerc_v04_0001",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "What's up?",
+  "fps": 30.0,
+  "n_frames": 139,
+  "phrase_id": 1,
+  "parallel": true,
+  "hand_slots": "verified",
+  "segments": [
+    { "gloss": "WHAT'S UP", "start": 0.9, "end": 1.4 },
+    { "gloss": "QUESTION",  "start": 2.0, "end": 2.8 }
+  ]
+}
+```
+
+`phrase_id` identifies the phrase, not the clip: two clips sharing a `phrase_id`
+are two signers' renderings of the same phrase, and their `text_en` strings are
+identical by construction. `parallel` is `true` for the 5-signer grid and
+`false` for the three own-register signers: FOXTROT (`phrase_id` 1001-1300), GOLF (2001-2300) and
+HOTEL (3001-3300). `hand_slots` is `verified` or `unverified` (see the correction note).
+
+### metadata.csv columns
+
+| Column | Meaning |
+|---|---|
+| `clip_id` | `clerc_v04_0001` … `clerc_v04_2400` |
+| `signer_id` | pseudonym, ALPHA … HOTEL |
+| `phrase_id` | phrase identity, shared across signers (see above) |
+| `parallel` | `yes` inside the 5-signer grid, `no` for FOXTROT, GOLF, HOTEL |
+| `text_en` | English phrase, identical for a given `phrase_id` |
+| `fps`, `n_frames` | clip timing |
+| `oval_detection` | fraction of frames where the head silhouette was found |
+| `hand_slots` | `verified` if the hand-slot convention was checked against the pose, else `unverified` |
+| `gloss_sequence` | ` \| `-joined glosses, in order |
+
+---
+
+## Signers
+
+| signer_id | Gender | Age range | Language acquisition | Clips | Grid |
+|-----------|--------|-----------|---------------------|-------|------|
+| ALPHA | F | 30–40 | Native Deaf signer (ASL L1) | clerc_v04_0001 → 0300 | parallel |
+| BRAVO | M | 30–40 | Native Deaf signer (ASL L1) | clerc_v04_0301 → 0600 | parallel |
+| CHARLIE | M | 30–40 | Native Deaf signer (ASL L1) | clerc_v04_0601 → 0900 | parallel |
+| DELTA | F | 30–40 | Native Deaf signer (ASL L1) | clerc_v04_0901 → 1200 | parallel |
+| ECHO | F | 18–24 | Native Deaf signer (ASL L1) | clerc_v04_1201 → 1500 | parallel |
+| FOXTROT | M | 35–45 | Native Deaf signer (ASL L1) | clerc_v04_1501 → 1800 | own set |
+| GOLF | M | 18–24 | Deaf signer, fluent ASL (L2) | clerc_v04_1801 → 2100 | own set |
+| HOTEL | F | 30–40 | Native Deaf signer (ASL L1) | clerc_v04_2101 → 2400 | own set |
+
+**Demographic distribution:** 4 female / 4 male, aged 18–45. Signer identities are pseudonymized. ALPHA–FOXTROT are the same six signers as v0.3, under the same pseudonyms and with their v0.3 recordings kept for every phrase already published.
+
+Signers participated under written informed consent. The signing space, framing, lighting, and recording protocol were standardized across signers.
+
+**Parallel structure:** five signers (ALPHA–ECHO) cover a grid of 302 phrases. Pair renderings through the `phrase_id` column rather than by arithmetic on `clip_id`: 5 signers on 298 phrases, 4 signers on 2 phrases, 1 signer on 2 phrases. The phrases at four signers are ECHO's gaps (one v0.2 phrase she did not record, one rendering withdrawn for privacy in v0.4); the phrases at one signer are extras recorded by ECHO alone to bring her block to 300.
+
+**FOXTROT, GOLF and HOTEL are deliberately not parallel.** Each was recorded on a prompt set of full declarative sentences rather than the short conversational phrases and number expressions of the grid, and the three sets do not overlap. Aligning them would have meant dropping them. They are included as own registers, 300 phrases each, unique to that signer. Filter on `parallel == "no"` to isolate them, or on `parallel == "yes"` for strictly comparable inter-signer work.
+
+**Stylistic note:** Phrase repetition rates vary by signer - natural inter-signer stylistic variation, annotated as separate gloss segments. See gloss conventions for filtering.
+
+---
+
+## Intended Use
+
+### Designed for
+- Inter-signer variability analysis (style, rhythm, signing space)
+- Research on sign language linguistics, gesture recognition, multimodal AI
+- Educational use in academic settings
+- Prototyping sign language recognition (SLR) pipelines on a parallel multi-signer corpus
+
+### Not designed for
+- Speaker identification or biometric applications
+- Surveillance or evaluation of individual signers
+
+For production-grade systems or sign language generation models trained at scale, see commercial licensing for access to the full multi-signer corpus.
+
+---
+
+## Loading the Dataset
+
+This release ships as plain `.npy` + `.json` files for transparency and zero-dependency loading.
+
+```python
+import json
+import numpy as np
+import pandas as pd
+from pathlib import Path
+from huggingface_hub import snapshot_download
+
+ROOT = Path(snapshot_download(repo_id="CLERC-DATA/epee", repo_type="dataset"))
+
+metadata = pd.read_csv(ROOT / "metadata.csv")
+
+clip_id = "clerc_v04_0001"
+with open(ROOT / "annotations" / f"{clip_id}.json") as f:
+    annotation = json.load(f)
+keypoints = np.load(ROOT / "keypoints" / f"{clip_id}.npy")
+
+hands       = keypoints[:, :42]
+upper_body  = keypoints[:, 42:54]
+face_inner  = keypoints[:, 64:92]
+head_oval   = keypoints[:, 92:128]
+```
+
+**Comparing signers on the same phrase** - group by `phrase_id` inside the parallel grid:
+
+```python
+grid = metadata[metadata.parallel == "yes"]
+for phrase_id, group in grid.groupby("phrase_id"):
+    # one row per signer, same text_en, directly comparable
+    print(phrase_id, group.text_en.iloc[0], list(group.signer_id))
+```
+
+---
+
+## License
+
+**CC BY-NC-SA 4.0** - [creativecommons.org/licenses/by-nc-sa/4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)
+
+**Commercial licensing:** for enterprise use, training of commercial models, or integration into commercial products, contact **florian@clerc.io**.
+
+---
+
+## Ethical Considerations
+
+CLERC is Deaf-led infrastructure. This release adheres to:
+
+- **Informed consent** - all signers have provided written consent for public release under this license
+- **Privacy protection** - no video, no pixels; face landmarks restricted to non-identifying features (eyes + mouth + head outline), no face mesh, no blendshapes
+- **Community benefit** - released to advance sign language technology research; commercial revenue supports continued Deaf-led data infrastructure
+- **No surveillance use** - must not be used for individual identification, behavioral profiling, or signer surveillance
+
+### Skeletons are body data
+
+Removing the video removes the face, not the body. Body proportions in keypoint
+data act as a **soft biometric**: on this release, a plain logistic regression
+separates the six v0.3 signers with **94% accuracy from nine limb-ratio features
+alone** (chance is 17%), using no hand and no face landmarks at all. We measured
+this rather than assume it, and we state it rather than let "anonymized
+skeletons" imply more than it delivers.
+
+What this means for you as a user of this data:
+
+- Pseudonymization here protects **names, not bodies**. `ALPHA` is a stable
+  identity across clips and across CLERC releases, by design, because parallel
+  analysis requires it.
+- Linking these skeletons to any other recording of the same person, in this
+  dataset or outside it, is **identification**, and it is prohibited under the
+  no-surveillance term above regardless of technical feasibility.
+- If you redistribute derivatives under the share-alike term, this property
+  travels with them. Carry this note forward.
+
+We are a Deaf-led organization publishing data about Deaf bodies. Naming this
+limitation is part of the job, not an admission against interest.
+
+---
+
+## Limitations
+
+- **Pilot release** - 2,400 clips is a baseline pilot, not a production-scale corpus
+- **8 signers** - limited inter-signer diversity; full catalog includes a broader signer pool
+- **Three signers outside the grid** - FOXTROT, GOLF and HOTEL are not phrase-matched to the others, so strictly parallel analyses run on 1,500 clips, not 2,400
+- **A few clips with unverified hand slots** - 5 clips had too little hand evidence to check, see `hand_slots`
+- **Uneven grid coverage** - 5 signers on 298 phrases, 4 signers on 2 phrases, 1 signer on 2 phrases inside the grid
+- **Phrase domain** - conversational phrases, number expressions, and (FOXTROT, GOLF, HOTEL) general declarative sentences; not domain-specific (medical, legal, technical)
+- **Reduced face landmarks** - full facial grammar (brow, cheeks, head tilt) not included
+- **Gloss only** - no morphological, prosodic, or spatial annotation layers in v0.4
+- **Skeletons are a soft biometric** - signer identity is recoverable from body proportions (see Ethical Considerations); treat pseudonyms as stable identities, not as anonymity
+
+---
+
+## Versioning & Roadmap
+
+| Version | Status | Content |
+|---------|--------|---------|
+| v0.1 | Superseded | 300 clips, 3 signers, gloss + timing |
+| v0.2 | Superseded | 600 clips, 4 signers (ALPHA–DELTA), 150 parallel phrases |
+| v0.3 | Superseded | 1,200 clips, 6 signers (ALPHA–FOXTROT), 201-phrase grid + a second register (crossed hand slots) |
+| **v0.4** | ✅ Current | 2,400 clips, 8 signers (ALPHA–HOTEL), 302-phrase grid + three own registers, hand slots fixed |
+| v1.0 | Planned 2027 | Multi-layer annotations, broader corpus |
+
+Superseded versions stay reachable as git tags on this repo (`v0.1`, `v0.2`, `v0.3`), so
+earlier clip ids remain resolvable for anyone who cited them:
+
+```python
+snapshot_download(repo_id="CLERC-DATA/epee", repo_type="dataset", revision="v0.3")
+```
+
+---
+
+## How to Cite
+
+```bibtex
+@dataset{clerc_epee_v04_2026,
+  author       = {M{\'e}loux, Florian and {CLERC}},
+  title        = {{CLERC} {\'E}p{\'e}e v0.4: Sign Language Data Layer},
+  year         = {2026},
+  publisher    = {Hugging Face},
+  version      = {0.4},
+  doi          = {10.5281/zenodo.23587708},
+  url          = {https://huggingface.co/datasets/CLERC-DATA/epee}
+}
+```
+
+---
+
+## About CLERC
+
+CLERC builds the data infrastructure that lets AI understand sign language as a first-class language - not an accessibility afterthought.
+
+> Sign language is not to be translated. It is to be inscribed.
+
+**Website:** [clerc.io](https://clerc.io) · **Contact:** florian@clerc.io · **LinkedIn:** [clerc-io](https://linkedin.com/company/clerc-io)
+
+---
+
+## Changelog
+
+**v0.4 - October 2026**
+- **Hand-slot correction.** v0.1 to v0.3 shipped with crossed hand slots (61.7% of decidable v0.3 clips). Every clip is now re-anchored to the Pose wrists and the built files are re-checked before release. New `hand_slots` column. See the correction note
+- Signer pool 6 → 8: added GOLF and HOTEL, each on an own prompt set. Corpus 1,200 → 2,400 clips, 300 per signer
+- Parallel grid widened 201 → 302 phrases across 5 signers. Phrase 201, ECHO-only in v0.3, is now signed by all five. 5 signers on 298 phrases, 4 signers on 2 phrases, 1 signer on 2 phrases
+- FOXTROT 200 → 300 clips on his own register (`phrase_id` 1001-1300)
+- Every v0.3 recording is kept for its phrase except one, withdrawn for privacy (a fill-in prompt answered with personal information); clips renumbered `clerc_v04_0001`–`clerc_v04_2400`, v0.3 ids stay resolvable under tag `v0.3`
+- Benchmark re-run 1 → 8 signers with hand slots fixed in train and test; the effect of the correction alone is reported separately
+- No clip and no new phrase of the sequestered Épée 200 exam is published
+
+**v0.3 - August 2026**
+- Signer pool 4 → 6: added ECHO and FOXTROT. Corpus 600 → 1,200 clips, 200 per signer
+- Parallel grid widened 150 → 201 phrases across 5 signers. 5 signers on 199 phrases, 4 signers on 1 phrase, 1 signer on 1 phrase
+- FOXTROT added as a second register: 200 declarative sentences on a prompt set disjoint from the grid, flagged `parallel = no`
+- New `phrase_id` and `parallel` fields in `metadata.csv` and in each annotation, so cross-signer pairing no longer depends on clip-id arithmetic
+- New `oval_detection` column reporting per-clip head-silhouette coverage
+- Clips renumbered `clerc_v03_0001`–`clerc_v03_1200`; v0.2 ids stay resolvable under tag `v0.2`
+- Head silhouette now extracted on a pose-guided head crop rather than the full frame. MediaPipe's face detector drops faces below roughly 8% of image width; on the clips where this happened the old path lost up to 21% of frames, the new one loses none. The 92 body/hand/face-subset keypoints are produced by the unchanged pipeline
+- The four v0.2 signers keep their pseudonyms and their original recordings for the 150 phrases already published
+- Signer-robustness benchmark re-run on the six v0.3 signers, same protocol, vocabulary and held-out signers as v0.2 - the two curves are directly comparable (v0.2 overlaid in the figure)
+- Added a measured statement on skeletons as a soft biometric, replacing the v0.2 card's "full biometric data excluded" wording, which overstated what removing video achieves
+
+**v0.2 - June 2026**
+- Added 4th signer (DELTA) and expanded to 600 clips
+- Restructured to 150 fully-parallel phrases × 4 signers (phrase-aligned clip blocks)
+- Same 128 multimodal keypoints/frame and gloss schema as v0.1
+
+**v0.1 - May 2026**
+- Initial public release - 300 clips, 3 signers, parallel structure

annotations/clerc_v04_0001.json

@@ -0,0 +1,18 @@
+{
+  "clip_id": "clerc_v04_0001",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "What’s up?",
+  "fps": 30.0,
+  "n_frames": 111,
+  "segments": [
+    {
+      "gloss": "WHAT'S UP",
+      "start": 1.0,
+      "end": 2.1
+    }
+  ],
+  "phrase_id": 1,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0002.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0002",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Do you see?",
+  "fps": 30.0,
+  "n_frames": 158,
+  "segments": [
+    {
+      "gloss": "D-O",
+      "start": 0.8,
+      "end": 1.1
+    },
+    {
+      "gloss": "YOU",
+      "start": 1.3,
+      "end": 1.5
+    },
+    {
+      "gloss": "SEE",
+      "start": 1.9,
+      "end": 2.3
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.6,
+      "end": 3.2
+    }
+  ],
+  "phrase_id": 2,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0003.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0003",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Are you tired?",
+  "fps": 30.0,
+  "n_frames": 114,
+  "segments": [
+    {
+      "gloss": "YOU",
+      "start": 0.7,
+      "end": 1.0
+    },
+    {
+      "gloss": "TIRED",
+      "start": 1.2,
+      "end": 1.9
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.2,
+      "end": 2.7
+    }
+  ],
+  "phrase_id": 3,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0004.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0004",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Are you hungry?",
+  "fps": 30.0,
+  "n_frames": 124,
+  "segments": [
+    {
+      "gloss": "YOU",
+      "start": 0.5,
+      "end": 0.9
+    },
+    {
+      "gloss": "HUNGRY",
+      "start": 1.1,
+      "end": 1.5
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 1.8,
+      "end": 2.3
+    }
+  ],
+  "phrase_id": 4,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0005.json

@@ -0,0 +1,38 @@
+{
+  "clip_id": "clerc_v04_0005",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Where do you live?",
+  "fps": 30.0,
+  "n_frames": 142,
+  "segments": [
+    {
+      "gloss": "WHERE",
+      "start": 0.4,
+      "end": 1.0
+    },
+    {
+      "gloss": "D-O",
+      "start": 1.3,
+      "end": 1.5
+    },
+    {
+      "gloss": "YOU",
+      "start": 1.7,
+      "end": 1.9
+    },
+    {
+      "gloss": "LIVE_2",
+      "start": 2.1,
+      "end": 2.6
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.8,
+      "end": 3.5
+    }
+  ],
+  "phrase_id": 5,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0006.json

@@ -0,0 +1,38 @@
+{
+  "clip_id": "clerc_v04_0006",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Do you need to help?",
+  "fps": 30.0,
+  "n_frames": 164,
+  "segments": [
+    {
+      "gloss": "D-O",
+      "start": 0.7,
+      "end": 1.0
+    },
+    {
+      "gloss": "YOU",
+      "start": 1.1,
+      "end": 1.4
+    },
+    {
+      "gloss": "NEED",
+      "start": 1.5,
+      "end": 1.9
+    },
+    {
+      "gloss": "HELP",
+      "start": 2.1,
+      "end": 3.3
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 3.5,
+      "end": 4.2
+    }
+  ],
+  "phrase_id": 6,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0007.json

@@ -0,0 +1,48 @@
+{
+  "clip_id": "clerc_v04_0007",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "How old are you?",
+  "fps": 30.0,
+  "n_frames": 213,
+  "segments": [
+    {
+      "gloss": "HOW",
+      "start": 0.7,
+      "end": 1.0
+    },
+    {
+      "gloss": "OLD",
+      "start": 1.2,
+      "end": 1.5
+    },
+    {
+      "gloss": "YOU",
+      "start": 2.1,
+      "end": 2.5
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.7,
+      "end": 3.3
+    },
+    {
+      "gloss": "OLD",
+      "start": 3.7,
+      "end": 4.6
+    },
+    {
+      "gloss": "YOU",
+      "start": 4.8,
+      "end": 5.1
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 5.3,
+      "end": 5.8
+    }
+  ],
+  "phrase_id": 7,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0008.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0008",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "How do you feel?",
+  "fps": 30.0,
+  "n_frames": 139,
+  "segments": [
+    {
+      "gloss": "HOW",
+      "start": 0.7,
+      "end": 1.1
+    },
+    {
+      "gloss": "YOU",
+      "start": 1.4,
+      "end": 1.6
+    },
+    {
+      "gloss": "FEEL",
+      "start": 1.9,
+      "end": 2.7
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.9,
+      "end": 3.4
+    }
+  ],
+  "phrase_id": 8,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0009.json

@@ -0,0 +1,18 @@
+{
+  "clip_id": "clerc_v04_0009",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Thank you",
+  "fps": 30.0,
+  "n_frames": 118,
+  "segments": [
+    {
+      "gloss": "THANK YOU",
+      "start": 0.9,
+      "end": 2.6
+    }
+  ],
+  "phrase_id": 9,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0010.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0010",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "I do not understand",
+  "fps": 30.0,
+  "n_frames": 148,
+  "segments": [
+    {
+      "gloss": "I",
+      "start": 0.6,
+      "end": 1.0
+    },
+    {
+      "gloss": "DON'T",
+      "start": 1.2,
+      "end": 1.5
+    },
+    {
+      "gloss": "UNDERSTAND",
+      "start": 1.7,
+      "end": 3.1
+    }
+  ],
+  "phrase_id": 10,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0011.json

@@ -0,0 +1,18 @@
+{
+  "clip_id": "clerc_v04_0011",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Hello",
+  "fps": 30.0,
+  "n_frames": 137,
+  "segments": [
+    {
+      "gloss": "HELLO",
+      "start": 1.1,
+      "end": 3.3
+    }
+  ],
+  "phrase_id": 11,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0012.json

@@ -0,0 +1,43 @@
+{
+  "clip_id": "clerc_v04_0012",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Nice to meet you",
+  "fps": 30.0,
+  "n_frames": 173,
+  "segments": [
+    {
+      "gloss": "NICE",
+      "start": 0.5,
+      "end": 1.0
+    },
+    {
+      "gloss": "MEET",
+      "start": 1.3,
+      "end": 1.5
+    },
+    {
+      "gloss": "YOU",
+      "start": 1.8,
+      "end": 2.3
+    },
+    {
+      "gloss": "NICE",
+      "start": 2.9,
+      "end": 3.5
+    },
+    {
+      "gloss": "MEET",
+      "start": 3.7,
+      "end": 4.1
+    },
+    {
+      "gloss": "YOU",
+      "start": 4.3,
+      "end": 4.8
+    }
+  ],
+  "phrase_id": 12,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0013.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0013",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Good morning",
+  "fps": 30.0,
+  "n_frames": 163,
+  "segments": [
+    {
+      "gloss": "GOOD",
+      "start": 0.6,
+      "end": 1.1
+    },
+    {
+      "gloss": "MORNING",
+      "start": 1.4,
+      "end": 2.3
+    },
+    {
+      "gloss": "GOOD",
+      "start": 2.8,
+      "end": 3.2
+    },
+    {
+      "gloss": "MORNING",
+      "start": 3.5,
+      "end": 4.3
+    }
+  ],
+  "phrase_id": 13,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0014.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0014",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Good afternoon",
+  "fps": 30.0,
+  "n_frames": 161,
+  "segments": [
+    {
+      "gloss": "GOOD",
+      "start": 0.7,
+      "end": 1.1
+    },
+    {
+      "gloss": "AFTERNOON",
+      "start": 1.3,
+      "end": 2.3
+    },
+    {
+      "gloss": "GOOD",
+      "start": 2.9,
+      "end": 3.3
+    },
+    {
+      "gloss": "AFTERNOON",
+      "start": 3.6,
+      "end": 4.5
+    }
+  ],
+  "phrase_id": 14,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0015.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0015",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Good evening",
+  "fps": 30.0,
+  "n_frames": 158,
+  "segments": [
+    {
+      "gloss": "GOOD",
+      "start": 0.4,
+      "end": 0.9
+    },
+    {
+      "gloss": "NIGHT",
+      "start": 1.2,
+      "end": 2.4
+    },
+    {
+      "gloss": "GOOD",
+      "start": 2.8,
+      "end": 3.2
+    },
+    {
+      "gloss": "NIGHT",
+      "start": 3.6,
+      "end": 4.4
+    }
+  ],
+  "phrase_id": 15,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0016.json

@@ -0,0 +1,23 @@
+{
+  "clip_id": "clerc_v04_0016",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Goodbye",
+  "fps": 30.0,
+  "n_frames": 115,
+  "segments": [
+    {
+      "gloss": "GOOD BYE",
+      "start": 0.4,
+      "end": 2.0
+    },
+    {
+      "gloss": "GOOD BYE",
+      "start": 2.2,
+      "end": 3.6
+    }
+  ],
+  "phrase_id": 16,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0017.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0017",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "My name is ___",
+  "fps": 30.0,
+  "n_frames": 225,
+  "segments": [
+    {
+      "gloss": "MY",
+      "start": 0.4,
+      "end": 0.9
+    },
+    {
+      "gloss": "NAME",
+      "start": 1.2,
+      "end": 1.6
+    },
+    {
+      "gloss": "MY",
+      "start": 3.9,
+      "end": 4.4
+    },
+    {
+      "gloss": "NAME",
+      "start": 4.7,
+      "end": 5.3
+    }
+  ],
+  "phrase_id": 17,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0018.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0018",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "What is your name?",
+  "fps": 30.0,
+  "n_frames": 126,
+  "segments": [
+    {
+      "gloss": "WHAT",
+      "start": 0.4,
+      "end": 1.0
+    },
+    {
+      "gloss": "YOUR",
+      "start": 1.3,
+      "end": 1.6
+    },
+    {
+      "gloss": "NAME",
+      "start": 1.8,
+      "end": 2.4
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.7,
+      "end": 3.3
+    }
+  ],
+  "phrase_id": 18,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0019.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0019",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Are you hurt?",
+  "fps": 30.0,
+  "n_frames": 114,
+  "segments": [
+    {
+      "gloss": "YOU",
+      "start": 0.9,
+      "end": 1.2
+    },
+    {
+      "gloss": "HURT",
+      "start": 1.5,
+      "end": 2.7
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.8,
+      "end": 3.3
+    }
+  ],
+  "phrase_id": 19,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0020.json

@@ -0,0 +1,48 @@
+{
+  "clip_id": "clerc_v04_0020",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Where are you from?",
+  "fps": 30.0,
+  "n_frames": 172,
+  "segments": [
+    {
+      "gloss": "WHERE",
+      "start": 0.3,
+      "end": 0.7
+    },
+    {
+      "gloss": "YOU",
+      "start": 0.9,
+      "end": 1.2
+    },
+    {
+      "gloss": "FROM",
+      "start": 1.6,
+      "end": 2.2
+    },
+    {
+      "gloss": "WHERE",
+      "start": 2.5,
+      "end": 3.1
+    },
+    {
+      "gloss": "YOU",
+      "start": 3.3,
+      "end": 3.6
+    },
+    {
+      "gloss": "FROM",
+      "start": 3.8,
+      "end": 4.5
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 4.7,
+      "end": 5.2
+    }
+  ],
+  "phrase_id": 20,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0021.json

@@ -0,0 +1,43 @@
+{
+  "clip_id": "clerc_v04_0021",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Are you deaf?",
+  "fps": 30.0,
+  "n_frames": 149,
+  "segments": [
+    {
+      "gloss": "YOU",
+      "start": 0.3,
+      "end": 0.7
+    },
+    {
+      "gloss": "DEAF",
+      "start": 0.9,
+      "end": 1.5
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 1.7,
+      "end": 2.4
+    },
+    {
+      "gloss": "YOU",
+      "start": 2.6,
+      "end": 3.0
+    },
+    {
+      "gloss": "DEAF",
+      "start": 3.2,
+      "end": 3.8
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 4.0,
+      "end": 4.5
+    }
+  ],
+  "phrase_id": 21,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0022.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0022",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Are you student?",
+  "fps": 30.0,
+  "n_frames": 122,
+  "segments": [
+    {
+      "gloss": "YOU",
+      "start": 0.3,
+      "end": 0.8
+    },
+    {
+      "gloss": "STUDENT",
+      "start": 1.2,
+      "end": 2.4
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.7,
+      "end": 3.5
+    }
+  ],
+  "phrase_id": 22,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0023.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0023",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Who is your teacher ?",
+  "fps": 30.0,
+  "n_frames": 144,
+  "segments": [
+    {
+      "gloss": "WHO",
+      "start": 0.3,
+      "end": 1.1
+    },
+    {
+      "gloss": "YOUR",
+      "start": 1.3,
+      "end": 1.6
+    },
+    {
+      "gloss": "TEACHER",
+      "start": 1.9,
+      "end": 3.2
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 3.3,
+      "end": 4.3
+    }
+  ],
+  "phrase_id": 23,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0024.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0024",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Do you have backpack?",
+  "fps": 30.0,
+  "n_frames": 131,
+  "segments": [
+    {
+      "gloss": "YOU",
+      "start": 0.2,
+      "end": 0.6
+    },
+    {
+      "gloss": "HAVE",
+      "start": 0.9,
+      "end": 1.2
+    },
+    {
+      "gloss": "BACKPACK",
+      "start": 1.4,
+      "end": 2.6
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.9,
+      "end": 3.6
+    }
+  ],
+  "phrase_id": 24,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0025.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0025",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Where is the bathroom",
+  "fps": 30.0,
+  "n_frames": 167,
+  "segments": [
+    {
+      "gloss": "WHERE",
+      "start": 0.5,
+      "end": 1.4
+    },
+    {
+      "gloss": "BATHROOM",
+      "start": 1.7,
+      "end": 2.5
+    },
+    {
+      "gloss": "WHERE",
+      "start": 2.9,
+      "end": 3.6
+    },
+    {
+      "gloss": "BATHROOM",
+      "start": 3.9,
+      "end": 4.4
+    }
+  ],
+  "phrase_id": 25,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0026.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0026",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Are you crying?",
+  "fps": 30.0,
+  "n_frames": 112,
+  "segments": [
+    {
+      "gloss": "YOU",
+      "start": 0.3,
+      "end": 0.8
+    },
+    {
+      "gloss": "CRY",
+      "start": 1.0,
+      "end": 2.4
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.5,
+      "end": 3.2
+    }
+  ],
+  "phrase_id": 26,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0027.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0027",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "How are you?",
+  "fps": 30.0,
+  "n_frames": 112,
+  "segments": [
+    {
+      "gloss": "HOW_RIGHT_MOVE",
+      "start": 0.7,
+      "end": 1.1
+    },
+    {
+      "gloss": "YOU",
+      "start": 1.2,
+      "end": 1.7
+    },
+    {
+      "gloss": "HOW",
+      "start": 2.2,
+      "end": 2.4
+    },
+    {
+      "gloss": "YOU",
+      "start": 2.5,
+      "end": 3.1
+    }
+  ],
+  "phrase_id": 27,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0028.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0028",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Are you cold?",
+  "fps": 30.0,
+  "n_frames": 113,
+  "segments": [
+    {
+      "gloss": "YOU",
+      "start": 0.9,
+      "end": 1.1
+    },
+    {
+      "gloss": "COLD",
+      "start": 1.3,
+      "end": 2.5
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.7,
+      "end": 3.3
+    }
+  ],
+  "phrase_id": 28,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0029.json

@@ -0,0 +1,43 @@
+{
+  "clip_id": "clerc_v04_0029",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Are you finished?",
+  "fps": 30.0,
+  "n_frames": 137,
+  "segments": [
+    {
+      "gloss": "YOU",
+      "start": 0.4,
+      "end": 0.7
+    },
+    {
+      "gloss": "FINISH",
+      "start": 0.9,
+      "end": 1.4
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 1.5,
+      "end": 2.4
+    },
+    {
+      "gloss": "YOU",
+      "start": 2.6,
+      "end": 2.9
+    },
+    {
+      "gloss": "FINISH",
+      "start": 3.1,
+      "end": 3.5
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 3.6,
+      "end": 4.3
+    }
+  ],
+  "phrase_id": 29,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0030.json

@@ -0,0 +1,53 @@
+{
+  "clip_id": "clerc_v04_0030",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Where is your bottle?",
+  "fps": 30.0,
+  "n_frames": 214,
+  "segments": [
+    {
+      "gloss": "WHERE",
+      "start": 0.3,
+      "end": 0.9
+    },
+    {
+      "gloss": "YOUR",
+      "start": 1.0,
+      "end": 1.3
+    },
+    {
+      "gloss": "BOTTLE",
+      "start": 1.5,
+      "end": 2.5
+    },
+    {
+      "gloss": "BOTTLE",
+      "start": 2.7,
+      "end": 3.5
+    },
+    {
+      "gloss": "WHERE",
+      "start": 3.8,
+      "end": 4.2
+    },
+    {
+      "gloss": "YOUR",
+      "start": 4.4,
+      "end": 4.6
+    },
+    {
+      "gloss": "BOTTLE",
+      "start": 5.0,
+      "end": 5.7
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 5.9,
+      "end": 6.4
+    }
+  ],
+  "phrase_id": 30,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0031.json

@@ -0,0 +1,33 @@
+{
+  "clip_id": "clerc_v04_0031",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Where is your banana?",
+  "fps": 30.0,
+  "n_frames": 152,
+  "segments": [
+    {
+      "gloss": "WHERE",
+      "start": 0.3,
+      "end": 0.7
+    },
+    {
+      "gloss": "YOUR",
+      "start": 0.9,
+      "end": 1.3
+    },
+    {
+      "gloss": "BANANA",
+      "start": 1.7,
+      "end": 3.4
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 3.5,
+      "end": 4.3
+    }
+  ],
+  "phrase_id": 31,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0032.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0032",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "What time is it?",
+  "fps": 30.0,
+  "n_frames": 117,
+  "segments": [
+    {
+      "gloss": "WHAT",
+      "start": 0.2,
+      "end": 0.7
+    },
+    {
+      "gloss": "TIME",
+      "start": 1.0,
+      "end": 2.1
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.3,
+      "end": 3.1
+    }
+  ],
+  "phrase_id": 32,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0033.json

@@ -0,0 +1,38 @@
+{
+  "clip_id": "clerc_v04_0033",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "What happened?",
+  "fps": 30.0,
+  "n_frames": 128,
+  "segments": [
+    {
+      "gloss": "DO",
+      "start": 0.4,
+      "end": 0.7
+    },
+    {
+      "gloss": "HAPPEN",
+      "start": 0.8,
+      "end": 1.2
+    },
+    {
+      "gloss": "DO",
+      "start": 1.5,
+      "end": 1.9
+    },
+    {
+      "gloss": "HAPPEN",
+      "start": 2.0,
+      "end": 2.4
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.6,
+      "end": 3.2
+    }
+  ],
+  "phrase_id": 33,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0034.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0034",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Are you happy?",
+  "fps": 30.0,
+  "n_frames": 90,
+  "segments": [
+    {
+      "gloss": "YOU",
+      "start": 0.4,
+      "end": 0.7
+    },
+    {
+      "gloss": "HAPPY",
+      "start": 1.0,
+      "end": 1.7
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 1.8,
+      "end": 2.6
+    }
+  ],
+  "phrase_id": 34,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0035.json

@@ -0,0 +1,38 @@
+{
+  "clip_id": "clerc_v04_0035",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Where are you go?",
+  "fps": 30.0,
+  "n_frames": 155,
+  "segments": [
+    {
+      "gloss": "WHERE",
+      "start": 0.4,
+      "end": 1.1
+    },
+    {
+      "gloss": "GO",
+      "start": 1.3,
+      "end": 1.8
+    },
+    {
+      "gloss": "WHERE",
+      "start": 2.0,
+      "end": 2.5
+    },
+    {
+      "gloss": "GO",
+      "start": 2.7,
+      "end": 3.2
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 3.4,
+      "end": 4.2
+    }
+  ],
+  "phrase_id": 35,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0036.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0036",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Why?",
+  "fps": 30.0,
+  "n_frames": 124,
+  "segments": [
+    {
+      "gloss": "WHY",
+      "start": 0.5,
+      "end": 1.3
+    },
+    {
+      "gloss": "WHY",
+      "start": 2.1,
+      "end": 3.1
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 3.4,
+      "end": 4.0
+    }
+  ],
+  "phrase_id": 36,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0037.json

@@ -0,0 +1,23 @@
+{
+  "clip_id": "clerc_v04_0037",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "How?",
+  "fps": 30.0,
+  "n_frames": 97,
+  "segments": [
+    {
+      "gloss": "HOW",
+      "start": 0.1,
+      "end": 1.8
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 1.9,
+      "end": 2.7
+    }
+  ],
+  "phrase_id": 37,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0038.json

@@ -0,0 +1,23 @@
+{
+  "clip_id": "clerc_v04_0038",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "When?",
+  "fps": 30.0,
+  "n_frames": 119,
+  "segments": [
+    {
+      "gloss": "WHEN",
+      "start": 0.1,
+      "end": 1.4
+    },
+    {
+      "gloss": "WHEN",
+      "start": 1.8,
+      "end": 2.5
+    }
+  ],
+  "phrase_id": 38,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0039.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0039",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Are you alright?",
+  "fps": 30.0,
+  "n_frames": 108,
+  "segments": [
+    {
+      "gloss": "YOU",
+      "start": 0.1,
+      "end": 0.6
+    },
+    {
+      "gloss": "ALRIGHT",
+      "start": 1.0,
+      "end": 1.9
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.1,
+      "end": 2.9
+    }
+  ],
+  "phrase_id": 39,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0040.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0040",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "See you later",
+  "fps": 30.0,
+  "n_frames": 90,
+  "segments": [
+    {
+      "gloss": "SEE",
+      "start": 0.2,
+      "end": 0.9
+    },
+    {
+      "gloss": "YOU",
+      "start": 1.0,
+      "end": 1.3
+    },
+    {
+      "gloss": "LATER",
+      "start": 1.4,
+      "end": 2.0
+    }
+  ],
+  "phrase_id": 40,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0041.json

@@ -0,0 +1,23 @@
+{
+  "clip_id": "clerc_v04_0041",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Who?",
+  "fps": 30.0,
+  "n_frames": 84,
+  "segments": [
+    {
+      "gloss": "WHO",
+      "start": 0.0,
+      "end": 1.9
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.0,
+      "end": 2.6
+    }
+  ],
+  "phrase_id": 41,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0042.json

@@ -0,0 +1,23 @@
+{
+  "clip_id": "clerc_v04_0042",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Which?",
+  "fps": 30.0,
+  "n_frames": 80,
+  "segments": [
+    {
+      "gloss": "WHICH",
+      "start": 0.0,
+      "end": 1.7
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.0,
+      "end": 2.6
+    }
+  ],
+  "phrase_id": 42,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0043.json

@@ -0,0 +1,23 @@
+{
+  "clip_id": "clerc_v04_0043",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Where?",
+  "fps": 30.0,
+  "n_frames": 69,
+  "segments": [
+    {
+      "gloss": "WHERE",
+      "start": 0.1,
+      "end": 1.3
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 1.5,
+      "end": 2.2
+    }
+  ],
+  "phrase_id": 43,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0044.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0044",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "What?",
+  "fps": 30.0,
+  "n_frames": 112,
+  "segments": [
+    {
+      "gloss": "WHAT_2",
+      "start": 0.1,
+      "end": 1.3
+    },
+    {
+      "gloss": "WHAT_2",
+      "start": 1.5,
+      "end": 2.3
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.6,
+      "end": 3.1
+    }
+  ],
+  "phrase_id": 44,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0045.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0045",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Any help?",
+  "fps": 30.0,
+  "n_frames": 116,
+  "segments": [
+    {
+      "gloss": "ANY",
+      "start": 0.2,
+      "end": 1.2
+    },
+    {
+      "gloss": "HELP",
+      "start": 1.4,
+      "end": 2.1
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 2.2,
+      "end": 3.1
+    }
+  ],
+  "phrase_id": 45,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0046.json

@@ -0,0 +1,23 @@
+{
+  "clip_id": "clerc_v04_0046",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "No problem",
+  "fps": 30.0,
+  "n_frames": 96,
+  "segments": [
+    {
+      "gloss": "NO",
+      "start": 0.1,
+      "end": 0.8
+    },
+    {
+      "gloss": "PROBLEM",
+      "start": 1.1,
+      "end": 2.3
+    }
+  ],
+  "phrase_id": 46,
+  "parallel": true,
+  "hand_slots": "verified"
+}

annotations/clerc_v04_0047.json

@@ -0,0 +1,28 @@
+{
+  "clip_id": "clerc_v04_0047",
+  "signer_id": "ALPHA",
+  "sign_language": "ASL",
+  "text_en": "Really?",
+  "fps": 30.0,
+  "n_frames": 124,
+  "segments": [
+    {
+      "gloss": "REALLY?",
+      "start": 0.3,
+      "end": 1.7
+    },
+    {
+      "gloss": "REALLY?",
+      "start": 1.8,
+      "end": 2.9
+    },
+    {
+      "gloss": "QUESTION",
+      "start": 3.1,
+      "end": 3.4
+    }
+  ],
+  "phrase_id": 47,
+  "parallel": true,
+  "hand_slots": "verified"
+}