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/compare_asr_content.py

@@ -10,7 +10,7 @@ ASR方案内容对比分析
 
 import json
 from pathlib import Path
-from difflib import unified_diff, SequenceMatcher
+from difflib import SequenceMatcher
 
 def load_segments(json_path):
     """加载JSON文件中的segments"""
@@ -25,7 +25,7 @@ def compare_segments(seg_a, seg_b, name_a, name_b):
     print(f"{'='*60}")
     
     # 统计
-    print(f"\n【数量对比】")
+    print("\n【数量对比】")
     print(f"  {name_a}: {len(seg_a)} segments")
     print(f"  {name_b}: {len(seg_b)} segments")
     print(f"  差异: {len(seg_a) - len(seg_b)} segments")
@@ -34,7 +34,7 @@ def compare_segments(seg_a, seg_b, name_a, name_b):
     total_time_a = sum(s['end'] - s['start'] for s in seg_a)
     total_time_b = sum(s['end'] - s['start'] for s in seg_b)
     
-    print(f"\n【时间覆盖】")
+    print("\n【时间覆盖】")
     print(f"  {name_a}: {total_time_a:.2f}秒")
     print(f"  {name_b}: {total_time_b:.2f}秒")
     print(f"  差异: {total_time_a - total_time_b:.2f}秒")
@@ -48,11 +48,11 @@ def compare_segments(seg_a, seg_b, name_a, name_b):
     text_b_full = ' '.join(texts_b)
     similarity = SequenceMatcher(None, text_a_full, text_b_full).ratio()
     
-    print(f"\n【文本相似度】")
+    print("\n【文本相似度】")
     print(f"  相似度: {similarity*100:.1f}%")
     
     # 差异分析
-    print(f"\n【详细差异】")
+    print("\n【详细差异】")
     
     # 按时间对齐对比
     matched_diffs = []
@@ -98,7 +98,7 @@ def compare_segments(seg_a, seg_b, name_a, name_b):
         if len(matched_diffs) > 10:
             print(f"\n  ... 还有 {len(matched_diffs) - 10} 处差异")
     else:
-        print(f"  ✓ 无显著文本差异")
+        print("  ✓ 无显著文本差异")
     
     return {
         'segments_diff': len(seg_a) - len(seg_b),
@@ -122,10 +122,10 @@ def main():
     
     # 方案基本信息
     print("【测试方案】")
-    print(f"  方案A: faster-whisper small CPU")
-    print(f"  方案B: OpenAI whisper small CPU")
-    print(f"  方案D: OpenAI whisper medium CPU")
-    print(f"  方案C/E: MPS失败（不支持）")
+    print("  方案A: faster-whisper small CPU")
+    print("  方案B: OpenAI whisper small CPU")
+    print("  方案D: OpenAI whisper medium CPU")
+    print("  方案C/E: MPS失败（不支持）")
     print()
     
     # 三组对比
@@ -142,16 +142,16 @@ def main():
     print("="*60)
     
     print("\n【Segments数量】")
-    print(f"  方案A: 77 segments (最多)")
-    print(f"  方案B: 74 segments")
-    print(f"  方案D: 74 segments")
-    print(f"  结论: faster-whisper分割更细（+3 segments）")
+    print("  方案A: 77 segments (最多)")
+    print("  方案B: 74 segments")
+    print("  方案D: 74 segments")
+    print("  结论: faster-whisper分割更细（+3 segments）")
     
     print("\n【文本相似度】")
     print(f"  A vs B: {results['A_vs_B']['similarity']*100:.1f}%")
     print(f"  A vs D: {results['A_vs_D']['similarity']*100:.1f}%")
     print(f"  B vs D: {results['B_vs_D']['similarity']*100:.1f}%")
-    print(f"  结论: 三个方案文本高度相似")
+    print("  结论: 三个方案文本高度相似")
     
     print("\n【文本差异统计】")
     print(f"  A vs B: {results['A_vs_B']['text_diffs']}处差异")
@@ -159,9 +159,9 @@ def main():
     print(f"  B vs D: {results['B_vs_D']['text_diffs']}处差异")
     
     print("\n【方案D（medium）vs 方案B（small）】")
-    print(f"  Segments数量相同: 74条")
+    print("  Segments数量相同: 74条")
     print(f"  文本相似度: {results['B_vs_D']['similarity']*100:.1f}%")
-    print(f"  结论: medium模型无明显提升")
+    print("  结论: medium模型无明显提升")
     
     print()
     print("="*60)