Add floor-event timing objective and addressee diagnostics
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docs/easycom_floor_event_diagnostics.md
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docs/easycom_floor_event_diagnostics.md
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# EasyCom floor-event diagnosis: timing, objective, and addressee
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These three experiments explain why a dense future-activity oracle can retain
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reasonable mAP while response/yield event AP remains low. They are diagnostics,
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not three proposed paper contributions. Keep the primary paper protocol as the
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pre-boundary competing-risk evaluation until the evidence says otherwise.
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## What each experiment isolates
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| Diagnostic | Only intended change | If it improves clearly |
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|---|---|---|
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| pre-boundary vs post-boundary | whether the aggregate-other boundary has already been observed at the decision source | much of the error is boundary anticipation, not weak AV encoding |
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| dense activity head vs direct event head | future-state loss vs response/yield loss, using the same frozen inputs | the dense objective/ranking conversion is the main mismatch |
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| addressee vs zero-channel control | explicit past `Target_of_Speech == wearer_id` history | aggregate activity misses conversational routing information |
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Do not compare raw AP across the pre- and post-boundary protocols as if they
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were the same task. Compare methods within one timing protocol, and use the
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pre/post difference only as a difficulty decomposition.
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## Shared remote environment
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```bash
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cd /data1/yfzx/wangx/Code/icassp2027-experiment
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export DATASET_ROOT=/data1/yfzx/wangx/Datasets/easycom/extracted_easycom
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export FEATURE_ROOT=/data1/yfzx/wangx/Datasets/easycom/omni_features/open_stream_2fps_8s_last4_stack
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export TARGET_ROOT=/data1/yfzx/wangx/Datasets/easycom/easycom_target_frame
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export LOCAL_ROOT=/data1/yfzx/wangx/Datasets/easycom/omni_features/local_qwen_1s_encoded_tf4576
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export ORACLE_ROOT=/data1/yfzx/wangx/Datasets/easycom/omni_features/oracle_person_history_2s
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```
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Change only paths that differ on the remote host. The default feature mode is
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`open-stream-replay`.
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## 1. Post-boundary reactive diagnostic for the three existing runs
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Point the wrapper at already aligned inference directories. Each directory
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must contain `pred/Session_*.npy` and `valid/Session_*.npy`.
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```bash
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export POOLED_AV_RUN=/path/to/pooled_av_result
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export ORACLE_RUN=/path/to/aggregate_visible_oracle_result
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export MINIROAD_RUN=/path/to/converted_miniroada_result
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bash run_easycom_post_boundary_eval.sh
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```
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Without `CALIBRATION_SESSIONS`, the wrapper explicitly marks threshold results
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as exploratory and selects them in-sample. AP is still useful for this first
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diagnosis. For a confirmatory result, provide training-side predictions in the
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same run directories and use, for example:
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```bash
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export CALIBRATION_SESSIONS="Session_12"
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bash run_easycom_post_boundary_eval.sh
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```
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The JSON protocol ID becomes
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`wearer_floor_event_post_boundary_diagnostic_v1`. Simultaneous wearer changes
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at the observed boundary and zero-length windows before an immediate competing
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boundary are excluded and counted explicitly.
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## 2. Direct response/yield event head
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The direct probe uses frozen Omni states, the same mixed-audio vectors and the
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same `aggregate-visible` past-activity oracle. Its layer fusion, audio
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projection, oracle person attention and shared MLP trunk are the same
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`TurnPredictionHead` components as the dense oracle; only the final two-event
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readout and event loss differ. It trains on Sessions 4--11, selects epoch and
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thresholds on Session 12, and initially evaluates only Session 12. First run a
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one-epoch Session-11/12 shape, mask and checkpoint smoke test:
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```bash
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CUDA_VISIBLE_DEVICES=0 bash run_easycom_floor_event_probes.sh smoke
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```
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Then run the single aggregate oracle diagnosis:
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```bash
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CUDA_VISIBLE_DEVICES=0 \
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VARIANTS="aggregate-visible" \
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bash run_easycom_floor_event_probes.sh all 0
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```
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This is the clean comparison against the existing dense aggregate-visible
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oracle head. A large direct-head gain supports objective mismatch; a small gain
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means the oracle information itself is probably weak for the event decision.
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## 3. Addressee oracle with a capacity-matched control
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Run all three direct-probe variants:
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```bash
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CUDA_VISIBLE_DEVICES=0 bash run_easycom_floor_event_probes.sh all 0
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```
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The variants are:
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- `aggregate-visible`: 2 s aggregate activity plus observation mask;
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- `aggregate-visible-address-control`: the same input plus an all-zero channel;
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- `aggregate-visible-addressee`: the same input plus past bins in which a
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visible non-wearer was explicitly annotated as addressing wearer ID 2.
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`Group`, `None`, unknown and other-person targets are not coerced into reliable
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negative labels. The addressee channel is privileged, annotation-derived and
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analysis-only; it is not an online feature or a deployable causal input.
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The runner writes one `summary.json` and `metrics.csv` per variant and a compact
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`comparison_dev.csv`. Inspect that comparison before touching Sessions 1--3.
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## Optional frozen test evaluation
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Only after the variants, epochs and interpretation rule are fixed from Session
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12, apply the saved probes to official test Sessions 1--3:
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```bash
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CUDA_VISIBLE_DEVICES=0 bash run_easycom_floor_event_probes.sh test 0
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```
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This reuses the saved Session-12 thresholds and writes `comparison_test.csv`.
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Do not repeatedly inspect test results and redesign the probe.
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## Minimum interpretation rule
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For response, jointly inspect mean AP, 2 s AP, achieved response recall, false
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entry rate, and short-resume trigger rate. For yield, inspect mean AP, 2 s AP,
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achieved yield recall, and false-stop rate. Denominators and censoring counts
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must match before comparing variants.
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The three outcomes lead to different paper decisions:
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1. **Only post-boundary improves:** retain the main anticipation task and frame
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the difficulty as predicting a boundary before it is observable. Do not
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claim that a larger event head solves grounding.
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2. **Direct event supervision improves:** the main lesson is target alignment;
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build the method around event-aware adaptation and keep dense mAP secondary.
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3. **Addressee improves over both aggregate and zero control:** conversational
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routing is the missing information. This motivates a deployable addressee or
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addressedness estimator, but the oracle itself is not the method.
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4. **None improves:** the current timing-derived event definition or available
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observations are insufficient. Revisit annotation/task definition before a
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heavier fusion architecture.
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