Épée v0.4: 2,400 clips, 8 signers, 302-phrase parallel grid over 5 signers + 3 own registers, hand slots fixed and verified on every clip

BENCHMARK.md

@@ -1,95 +1,111 @@
-# Épée v0.3 · Signer-Robustness Benchmark
+# Épée v0.4 · Signer-Robustness Benchmark
 
 **What it shows:** signer variation is the core problem in sign-language AI, and the fix is
-*more native signers and more data*, not a bigger model. Re-measured on the six v0.3 signers
-with the exact v0.2 protocol, so the two releases are directly comparable.
+*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 the six signers in this release (ALPHA through FOXTROT) and tested on
-**two native Deaf signers with no clips in this release** (Signer A and Signer B, pseudonymized,
-from the broader CLERC corpus). The held-out signers recorded under the same protocol and share
-prompts with the release signers. That is by design, not leakage: same content, brand-new body,
-which is exactly the controlled comparison a signer-generalization test needs. No clip and no
-recording is shared between 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 (gloss) classification on the **same 24 glosses** as the v0.2 measurement (vocabulary frozen, not recomputed) |
-| Train | 1,393 gloss segments from the six release signers (858 in v0.2) |
-| Test | Signer A: 1,961 segments · Signer B: 1,453 segments |
+| 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** (the task is imbalanced; macro-F1 is the honest headline) |
-
-Everything pinned against v0.2: vocabulary and class order, held-out signers and their exact
-test segments, model, features, seeds, aggregation. Only the training pool changed.
-
----
+| Metrics | top-1 accuracy **and macro-F1** |
 
 ## Result 1 · More signers → better on a brand-new signer
 
-Tested on Signer A, never seen in training. Mean over all signer combinations at each size,
-as in v0.2 (v0.2 values in grey):
+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 | Accuracy | Macro-F1 | v0.2 accuracy |
+| # training signers | combinations | Accuracy | Macro-F1 |
 |---|---|---|---|
-| 1 | 29% ± 15 | 0.17 | 22% |
-| 2 | 47% ± 12 | 0.30 | 40% |
-| 3 | 57% ± 10 | 0.39 | 50% |
-| 4 | 63% ± 8 | 0.47 | 59% |
-| 5 | 65% ± 7 | 0.51 | - |
-| **6** | **69% ± 5** | **0.57** | - |
+| 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 |
 
-The curve keeps rising through six signers, and the run-to-run spread narrows from ±15 to ±5
-along the way. A signer the model *has* seen scores 73% (ceiling): **the stranger gap, 43 points
-at one training signer, is down to 3 points at six.** Confirmed on Signer B: 58% (54% in v0.2).
+A signer the model *has* seen scores 83% (ceiling). At eight training signers the stranger
+gap is **1 point**. Second stranger, Signer B: 69%.
 
-Every point also beats its v0.2 counterpart at the same signer count (29 vs 22, 47 vs 40, 57 vs
-50, 63 vs 59). Same protocol, so the lift is the data: 200 clips per signer instead of 150, and
-a wider phrase grid.
+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 → keeps climbing, not saturated
+## Result 2 · More data → still rising, more slowly
 
-Same held-out signer; training set grown by a clean random fraction of the six-signer pool:
+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 |
-|---|---|---|---|---|---|---|---|---|---|
-| Accuracy | 22% | 34% | 41% | 53% | 55% | 68% | 64% | 63% | **71%** |
-
-From 22% to 71% across the pool, above the v0.2 curve at almost every budget, and still rising
-at the largest size. The dip around 858 to 1,044 is within the ±5 run-to-run spread, not a trend.
+| 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% |
 
 ---
 
-## Takeaway
-
-> Trained on one Deaf signer, the recognizer gets **29%** on a signer it has never seen. Trained
-> on six, it reaches **69%**, three points under the 73% it scores on signers it knows. The
-> stranger gap is closing, and it is the data doing it: more signers, more clips per signer. This
-> is why CLERC builds the multi-signer data layer.
-
 ## Caveats
 
-- 24-gloss shared subset (frozen from v0.2 for comparability); the full vocabulary will differ,
-  but the *shape* (more signers/data → up) should hold.
-- FOXTROT covers 18 of the 24 glosses: his prompt set is a different register (declarative
-  sentences, not conversational phrases). On this conversational test signer, the five grid
-  signers alone reach 70.5%, statistically indistinguishable from the full six at 69.4%. His
-  contribution to the release is register and vocabulary breadth, not extra accuracy on this
-  particular test. Combinations that include him at small k pull the low end of the spread down,
-  which is part of why the k=1 std is wide.
-- The 5→6 rise in the table is partly composition: at k=5, the mean averages mixes where FOXTROT
-  replaces a grid signer (worst combo 58.4%). Read the trend, not any single step.
-- Measures generalization across signer **bodies**, not across topics; cross-vocabulary
-  generalization is a separate, harder test.
-- Small BiLSTM by design; a bigger model does not close the 1-signer-vs-6-signer gap, which is a
-  data property.
-- A correction to the v0.2 card's wording: the held-out signers do share prompts with the release
-  signers (same recording protocol). "No shared clips" is the true and relevant guarantee; the
-  earlier "no shared phrases" claim was inaccurate and is retired.
+- 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

@@ -14,7 +14,7 @@ tags:
 - accessibility
 - deaf
 - benchmark
-pretty_name: "CLERC Épée v0.3 - Sign Language Data Layer"
+pretty_name: "CLERC Épée v0.4 - Sign Language Data Layer"
 size_categories:
 - 1K<n<10K
 task_categories:
@@ -23,11 +23,11 @@ task_categories:
 - token-classification
 ---
 
-# CLERC Épée v0.3
+# CLERC Épée v0.4
 
 **The first AI-grade sign language data layer.**
 
-![clips](https://img.shields.io/badge/clips-1,200-10b981) ![duration](https://img.shields.io/badge/signed_duration-70.86_min-10b981) ![signers](https://img.shields.io/badge/Deaf_signers-6-10b981) ![phrases](https://img.shields.io/badge/parallel_grid-201_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)
+![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)
@@ -39,7 +39,7 @@ The corpus is built around one idea: **the same phrase, signed by several Deaf s
 
 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.
 
-**v0.3 expands the signer pool from 4 to 6 and the corpus from 600 to 1,200 clips**, widens the parallel grid from 150 to 201 phrases, and adds a signer recorded on a distinct register.
+**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.
 
@@ -55,7 +55,7 @@ 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 == 1]
+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)
 ```
@@ -66,29 +66,37 @@ Or in five minutes with the open Python toolkit: [`epee-asl-toolkit`](https://gi
 
 ## Dataset Summary
 
-- **1,200 ASL clips, 70.86 minutes of continuous signing** - 6 Deaf signers, 200 clips each
-- **Parallel grid** - 200 phrases signed by 5 of the 6 signers, for direct inter-signer variability analysis
-- **A second register** - the 6th signer (FOXTROT) contributes 200 declarative sentences from a disjoint prompt set, so the corpus is not only short conversational phrases
+- **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 **v0.3**, a pilot release representing a portion of the full CLERC catalog. Full corpus access available via commercial license.
+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 six release signers and tested on signers held **entirely outside** the
-training set shows the core result: **one signer does not generalize to a stranger, six do better than four.**
+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 → … → 6 signers, tested on a brand-new signer: **29% → 47% → 57% → 63% → 65% → 69%** accuracy (macro-F1 0.17 → 0.57).
-- More data keeps lifting it: **22% → 71%** as training examples grow (1,393 segments in the v0.3 pool vs 858 in v0.2).
-- Tested on two signers with **no clips in this release**, same 24-gloss subset and protocol as the v0.2 measurement, 8 seeds - the two curves are directly comparable and the v0.2 one is overlaid in the figure.
+- 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)**.
 
@@ -98,18 +106,19 @@ Full method, numbers, and honest caveats: **[BENCHMARK.md](BENCHMARK.md)**.
 
 | Metric | Value |
 |---|---|
-| Total clips | 1,200 (200 per signer) |
-| Signers | 6 (ALPHA, BRAVO, CHARLIE, DELTA, ECHO, FOXTROT) |
-| Parallel grid | 1,000 clips over 201 phrases (5 signers) |
-| Second register | 200 clips, 200 phrases (FOXTROT, disjoint prompt set) |
-| Unique phrases | 401 |
-| Total frames | 127,545 |
-| Mean clip length | 106 frames (≈ 3.5 s @ 30 fps) |
-| Total signed duration | 70.86 min |
-| Gloss tokens | 3,788 |
-| Unique glosses | 724 |
-| Mean segments per clip | 3.16 |
+| 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) |
 
@@ -117,16 +126,16 @@ Full method, numbers, and honest caveats: **[BENCHMARK.md](BENCHMARK.md)**.
 
 | # | Gloss | Tokens | % of corpus |
 |---|---|---|---|
-| 1 | YOU | 418 | 11.0% |
-| 2 | QUESTION | 293 | 7.7% |
-| 3 | WHAT | 83 | 2.2% |
-| 4 | HAVE | 77 | 2.0% |
-| 5 | WHERE | 68 | 1.8% |
-| 6 | LIKE | 63 | 1.7% |
-| 7 | YOUR | 58 | 1.5% |
-| 8 | I | 52 | 1.4% |
-| 9 | WANT | 52 | 1.4% |
-| 10 | HOW | 42 | 1.1% |
+| 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% |
 
 ---
 
@@ -141,8 +150,8 @@ Full method, numbers, and honest caveats: **[BENCHMARK.md](BENCHMARK.md)**.
 
 ```
 epee/
-├── keypoints/           # 1,200 .npy arrays, shape (n_frames, 128, 3)
-├── annotations/         # 1,200 .json files
+├── keypoints/           # 2,400 .npy arrays, shape (n_frames, 128, 3)
+├── annotations/         # 2,400 .json files
 └── metadata.csv         # master index (1 row per clip)
 ```
 
@@ -150,8 +159,8 @@ epee/
 
 | Indices | Region | Source | Notes |
 |---------|--------|--------|-------|
-| 0–20 | Left hand (21 points) | MediaPipe Hands | |
-| 21–41 | Right hand (21 points) | MediaPipe Hands | |
+| 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 |
@@ -175,6 +184,24 @@ kp_slr = np.concatenate([kp[:, :54], kp[:, 64:]], axis=1)  # → (n_frames, 118,
 
 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:
@@ -203,7 +230,7 @@ def has_repeat(segments):
 
 ```json
 {
-  "clip_id": "clerc_v03_0001",
+  "clip_id": "clerc_v04_0001",
   "signer_id": "ALPHA",
   "sign_language": "ASL",
   "text_en": "What's up?",
@@ -211,6 +238,7 @@ def has_repeat(segments):
   "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 }
@@ -221,19 +249,21 @@ def has_repeat(segments):
 `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 FOXTROT's own prompt set (whose `phrase_id`s start at 1001).
+`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_v03_0001` … `clerc_v03_1200` |
-| `signer_id` | pseudonym, ALPHA … FOXTROT |
+| `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 |
+| `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 |
 
 ---
@@ -242,20 +272,22 @@ identical by construction. `parallel` is `true` for the 5-signer grid and
 
 | signer_id | Gender | Age range | Language acquisition | Clips | Grid |
 |-----------|--------|-----------|---------------------|-------|------|
-| ALPHA | F | 30–40 | Native Deaf signer (ASL L1) | clerc_v03_0001 → 0200 | parallel |
-| BRAVO | M | 30–40 | Native Deaf signer (ASL L1) | clerc_v03_0201 → 0400 | parallel |
-| CHARLIE | M | 30–40 | Native Deaf signer (ASL L1) | clerc_v03_0401 → 0600 | parallel |
-| DELTA | F | 30–40 | Native Deaf signer (ASL L1) | clerc_v03_0601 → 0800 | parallel |
-| ECHO | F | 18–24 | Native Deaf signer (ASL L1) | clerc_v03_0801 → 1000 | parallel |
-| FOXTROT | M | 35–45 | Native Deaf signer (ASL L1) | clerc_v03_1001 → 1200 | own set |
+| 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:** 3 female / 3 male, aged 18–45. All native ASL signers (Deaf, ASL as first language). Signer identities are pseudonymized. ALPHA–DELTA are the same four signers as v0.2, under the same pseudonyms.
+**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 201 phrases. Pair renderings through the `phrase_id` column rather than by arithmetic on `clip_id`: 5 signers on 199 phrases, 4 signers on 1 phrase, 1 signers on 1 phrase. The two phrases below full coverage are a v0.2 phrase ECHO did not record, and one extra phrase recorded by ECHO alone to bring her block to 200.
+**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 signers 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 is deliberately not parallel.** He was recorded on a different prompt set: full declarative sentences rather than the short conversational phrases and number expressions of the grid. Only one of his phrases occurs in the other signers' material, so aligning him would have meant either 61 clips instead of 200, or dropping him. He is included as a second register, and his 200 phrases are unique to him. Filter on `parallel == "no"` to isolate him, or on `parallel == "yes"` for strictly comparable inter-signer work.
+**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.
 
@@ -292,7 +324,7 @@ ROOT = Path(snapshot_download(repo_id="CLERC-DATA/epee", repo_type="dataset"))
 
 metadata = pd.read_csv(ROOT / "metadata.csv")
 
-clip_id = "clerc_v03_0001"
+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")
@@ -335,7 +367,7 @@ CLERC is Deaf-led infrastructure. This release adheres to:
 
 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 signers with **94% accuracy from nine limb-ratio features
+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.
@@ -358,13 +390,14 @@ limitation is part of the job, not an admission against interest.
 
 ## Limitations
 
-- **Pilot release** - 1,200 clips is a baseline pilot, not a production-scale corpus
-- **6 signers** - limited inter-signer diversity; full catalog includes a broader signer pool
-- **One signer outside the grid** - FOXTROT's 200 clips are not phrase-matched to the others, so strictly parallel analyses run on 1,000 clips, not 1,200
-- **Uneven grid coverage** - 5 signers on 199 phrases, 4 signers on 1 phrase, 1 signers on 1 phrase inside the grid
-- **Phrase domain** - conversational phrases, number expressions, and (FOXTROT) general declarative sentences; not domain-specific (medical, legal, technical)
+- **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 signers 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 v0.3
+- **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
 
 ---
@@ -375,14 +408,15 @@ limitation is part of the job, not an admission against interest.
 |---------|--------|---------|
 | v0.1 | Superseded | 300 clips, 3 signers, gloss + timing |
 | v0.2 | Superseded | 600 clips, 4 signers (ALPHA–DELTA), 150 parallel phrases |
-| **v0.3** | ✅ Current | 1,200 clips, 6 signers (ALPHA–FOXTROT), 201-phrase grid + a second register |
+| 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`), so
+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="v0.2")
+snapshot_download(repo_id="CLERC-DATA/epee", repo_type="dataset", revision="v0.3")
 ```
 
 ---
@@ -390,13 +424,13 @@ snapshot_download(repo_id="CLERC-DATA/epee", repo_type="dataset", revision="v0.2
 ## How to Cite
 
 ```bibtex
-@dataset{clerc_epee_v03_2026,
+@dataset{clerc_epee_v04_2026,
   author       = {M{\'e}loux, Florian and {CLERC}},
-  title        = {{CLERC} {\'E}p{\'e}e v0.3: Sign Language Data Layer},
+  title        = {{CLERC} {\'E}p{\'e}e v0.4: Sign Language Data Layer},
   year         = {2026},
   publisher    = {Hugging Face},
-  version      = {0.3},
-  doi          = {10.5281/zenodo.22081248},
+  version      = {0.4},
+  doi          = {10.5281/zenodo.20268565},
   url          = {https://huggingface.co/datasets/CLERC-DATA/epee}
 }
 ```
@@ -415,12 +449,18 @@ CLERC builds the data infrastructure that lets AI understand sign language as a
 
 ## Changelog
 
-**Withdrawal - 19 October 2026**
-- One clip was withdrawn for privacy: its answer to a fill-in prompt contained personal information. 1,199 clips remain. Statistics on this card describe the original 1,200-clip release.
+**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 signers 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 signers on 1 phrase
+- Parallel grid widened 150 → 302 phrases across 5 signers. 5 signers on 298 phrases, 4 signers on 2 phrases, 1 signers on 2 phrases
 - 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

annotations/clerc_v03_0001.json

@@ -1,17 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0002.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0003.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0004.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0005.json

@@ -1,37 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0006.json

@@ -1,37 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0007.json

@@ -1,47 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0008.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0009.json

@@ -1,17 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0010.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0011.json

@@ -1,17 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0012.json

@@ -1,42 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0013.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0014.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0015.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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": "EVENING",
-      "start": 1.2,
-      "end": 2.4
-    },
-    {
-      "gloss": "GOOD",
-      "start": 2.8,
-      "end": 3.2
-    },
-    {
-      "gloss": "EVENING",
-      "start": 3.6,
-      "end": 4.4
-    }
-  ],
-  "phrase_id": 15,
-  "parallel": true
-}

annotations/clerc_v03_0016.json

@@ -1,22 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0017.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0018.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0019.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0020.json

@@ -1,47 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0021.json

@@ -1,42 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0022.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0023.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0024.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0025.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0026.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0027.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0028.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0029.json

@@ -1,42 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0030.json

@@ -1,52 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0031.json

@@ -1,32 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0032.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0033.json

@@ -1,37 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0034.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0035.json

@@ -1,37 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0036.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0037.json

@@ -1,22 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0038.json

@@ -1,22 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0039.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0040.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0041.json

@@ -1,22 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0042.json

@@ -1,22 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0043.json

@@ -1,22 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0044.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0045.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0046.json

@@ -1,22 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}

annotations/clerc_v03_0047.json

@@ -1,27 +0,0 @@
-{
-  "clip_id": "clerc_v03_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
-}