feat: enhance score fusion confidence range and adjust CLAP weight for improved accuracy

app/routes/analyze.py

@@ -13,10 +13,12 @@ Pipeline:
 
 from __future__ import annotations
 
+import asyncio
 import io
 import time
 import uuid
 from collections import defaultdict
+from concurrent.futures import ThreadPoolExecutor
 from typing import Optional, List, Dict, Any, Literal
 from fastapi import (
     APIRouter, File, UploadFile, Form,
@@ -83,6 +85,9 @@ clap_service = CLAPDetectorService()
 fst_service = FSTClientService()
 xai_service = get_xai_service()
 
+# Thread pool for CPU-bound audio analysis (feature extraction + vocal)
+_analysis_pool = ThreadPoolExecutor(max_workers=3)
+
 
 # ============================================
 # Response Models - Platform Uyumlu

app/services/score_fusion.py

@@ -25,7 +25,7 @@ class FusionResult:
     """Final fused detection result."""
 
     is_ai_generated: bool
-    confidence: float                   # 0.51 – 0.97
+    confidence: float                   # 0.03 – 0.97
     decision_source: str                # "auris_fusion"
     model_version: str                  # "auris-v1-fusion"
 
@@ -254,9 +254,10 @@ def _fuse(
     # Layer 1 — always present
     scores.append((local, 0.40, "auris_local"))
 
-    # Layer 2 — CLAP embeddings
+    # Layer 2 — CLAP embeddings (reduced weight if heuristic fallback)
     if clap and clap.available:
-        scores.append((clap.confidence, 0.20, "clap"))
+        clap_weight = 0.20 if clap.classifier_used == "clap_embedding" else 0.08
+        scores.append((clap.confidence, clap_weight, "clap"))
 
     # Layer 3 — FST external (highest individual accuracy)
     if fst and fst.available: