diff --git a/app/src/main/java/com/k2fsa/sherpa/onnx/MainActivity.kt b/app/src/main/java/com/k2fsa/sherpa/onnx/MainActivity.kt
index bda4460..b7bcb90 100644
--- a/app/src/main/java/com/k2fsa/sherpa/onnx/MainActivity.kt
+++ b/app/src/main/java/com/k2fsa/sherpa/onnx/MainActivity.kt
@@ -687,20 +687,38 @@ class MainActivity : AppCompatActivity() {
                                 val rseq = onsetSeq
                                 speakerCheckHandler.post {
                                     if (rseq != onsetSeq) return@post
-                                    val emb = SpeakerRecognition.computeEmbeddingFast(
+                                    val anchor = windowRefEmb ?: return@post
+                                    // 一级:快锚点相似度(灵敏);贴近锚点=同人,免准确复核
+                                    val fastEmb = SpeakerRecognition.computeEmbeddingFast(
+                                        slice, sampleRateInHz) ?: return@post
+                                    if (rseq != onsetSeq) return@post
+                                    val simFast = SpeakerRecognition.similarity(
+                                        fastEmb, anchor)
+                                    if (simFast >= emaAbsorbMin) return@post
+                                    // 二级:准确空间复核(2026-09-16 误报实锤:A 暂停
+                                    // 续说,fast 短窗 simA<0.5 误判新人→A 的续说句被切
+                                    // 成"已识别人2"首句)。同人暂停后短窗声纹弱,fast
+                                    // 不可信;CAM++ 准确空间同人 0.77~0.93 强分离:
+                                    // 注册表认得出(且是当前人)→ 撤销切换;认得出别人
+                                    // → 切给他;谁都认不出 → 才当新人
+                                    val emb = SpeakerRecognition.computeEmbedding(
                                         slice, sampleRateInHz) ?: return@post
                                     if (rseq != onsetSeq) return@post
-                                    val anchor = windowRefEmb ?: return@post
-                                    val simA = SpeakerRecognition.similarity(emb, anchor)
-                                    if (simA >= emaAbsorbMin) return@post
                                     val active = activeLabelForWindow
-                                    val known = rollingSpeakerSearch(emb)
+                                    val known = SpeakerRecognition.registry.search(
+                                        emb, speakerThreshold)
+                                        ?: nearestAttribution(
+                                            emb, SpeakerRecognition.registry,
+                                            verdictFallbackMin)
                                     if (known != null && known == active) return@post
                                     val label = known
                                         ?: SpeakerRecognition.nextAutoLabel().also {
-                                            SpeakerRecognition.fastRegistry.addAuto(it, emb)
+                                            SpeakerRecognition.registry.addAuto(it, emb)
+                                            SpeakerRecognition.fastRegistry.addAuto(
+                                                it, fastEmb)
                                         }
-                                    Log.i(TAG, "ONSET-SWITCH simA=${"%.2f".format(simA)}" +
+                                    Log.i(TAG, "ONSET-SWITCH fastSim=" +
+                                            "%.2f".format(simFast) +
                                             " label=$label kind=" +
                                             (if (known != null) "known" else "new") +
                                             " active=${active ?: "-"}")