Performance: drop CNN KWS row (fallback only); clarify KWS is primarily text-based (Whisper)

Rewrite README to current pipeline (5-class taxonomy, PANNs SED/event_type, DANGER/CAUTION alerts; drop legacy SSLAM SED/Type heads)

Sync model file list: add panns_emg4_head.npz, drop legacy sed_head/emergency_type

Remove legacy checkpoints/sed_head.pth

Remove legacy checkpoints/emergency_type.pth

Add panns_emg4_head.npz (event_type acoustic head)

docs: add 2-track DeepFusion emotion model (69.3%) to model card

feat: add 2-track DeepFusion emotion model (KESDy18, 69.3% acc)

chore: remove undeployed emotion_head.pth (rule-based emotion is active)

docs: remove undeployed Emotion MLP from model card

docs: remove legacy checkpoint rows, explain text KWS has no custom weights

chore: remove unused legacy checkpoint checkpoints/emergency_decision.pth

chore: remove unused legacy checkpoint checkpoints/kws_model_sslam.pth

chore: remove unused legacy checkpoint checkpoints/kws_model.pth

feat: update kws_model_cnn.pth to 6-class multiclass (2026-06-10 retrain)

docs: clarify KWS checkpoints (active vs legacy) and add text KWS row

docs: add full per-component performance (SED, TypeClassifier, VA MAE, latency)

docs: update model card to current architecture (BinaryClassifier main, 2-stage KWS, rule-based emotion)

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initial commit