cleanup: remove dead code and duplicate docs

- Remove session-ses_2f27.md (161KB raw session log)
- Remove 49 ROOT_* duplicate files across REFERENCE/
- Remove 14 duplicate files between REFERENCE/ root and history/
- Remove asr_legacy.rs (dead code, replaced by asr.rs)
- Remove src/core/worker/ (duplicate JobWorker)
- Remove src/core/layers/ (empty directory)
- Remove 4 .bak files in src/
- Remove 7 dead private methods in worker/processor.rs
- Remove backup directory from git tracking

scripts/voice_embedding_extractor.py

@@ -12,7 +12,6 @@ import torch
 import librosa
 import numpy as np
 import psycopg2
-from psycopg2.extras import execute_values
 
 sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 
@@ -55,7 +54,7 @@ def extract_speaker_embeddings(uuid: str, video_path: str):
 
     # 2. 加載聲紋模型 (ECAPA-TDNN)
     # 注意：首次運行會下載模型 (~50MB)
-    print(f"  [Model] Loading SpeechBrain EncoderClassifier...")
+    print("  [Model] Loading SpeechBrain EncoderClassifier...")
     try:
         classifier = EncoderClassifier.from_hparams(
             source="speechbrain/spkrec-ecapa-voxceleb",