diff --git a/CHECKLIST.md b/CHECKLIST.md
index 772affd..d85c25d 100644
--- a/CHECKLIST.md
+++ b/CHECKLIST.md
@@ -160,7 +160,7 @@
   - 实测证据（`bench/reports/ASR.md`，`.venv/bin/python -m bench.asr_check` 生成）：3 段 Video-MME 真视频
     **258.18 秒**音频（容器时长 88.93 / 109.18 / 60.07），对着第三方字幕 WER **0.242**——分母是
     **533 个参考词**（听到 563 个词），三行各自的参考词数是 201 / 296 / 36。CPU int8 4 线程
-    3.55 秒转完，逐行 61.6× / 73.0× / 97.7× 实时。走产品路径摄入后从库里读回：**80 个 audio atom**、
+    3.26 秒转完，逐行 63.9× / 82.4× / 112.2× 实时。走产品路径摄入后从库里读回：**80 个 audio atom**、
     **563 个词级时间戳**、0 个时序倒错、0 个早于自己所属片段（总共 133 个 atom）。模型
     `Systran/faster-whisper-tiny`（78.2MB，model.bin sha256 dcb76c6586fc06cb…），远低于 500MB 上限。
   - 可复现性是量出来的：解码参数钉死 `beam_size=1, temperature=(0.0,), condition_on_previous_text=False,
@@ -183,7 +183,7 @@
     - 同一个静默毛病还有一处被 review 抓出来：`_ingest_text` 对超过 `max_text_file_bytes`（10 MiB）
       的文件也是直接返回空 batch。本仓库自己的语料里就有 277MB 的 `longmemeval_s_cleaned.json`。
       现在抛 `FileTooLarge`（带字节数和上限），扫描照样记进 `skipped`。
-    - 视频现在除了帧 atom 还会产出 speech atom（同一个 mp4：18 帧 + 31 段语音）。
+    - 视频现在除了帧 atom 还会产出 speech atom（同一个 mp4：18 帧 + 38 段语音，即 38 个 audio atom）。
     - 顺手把 p2-4 提前做了：`ingestion.py` 748 行超了 500 规则，拆成
       `ingestion_common.py`(102) / `ingestion_media.py`(ABC mixin, 278) / `ingestion_repository.py`(321) /
       `ingestion.py`(177)；`cli.py` 544 行也超了，按已有的 `cli_transactive.register` 模式拆出
diff --git a/backend/src/ely_eye/asr.py b/backend/src/ely_eye/asr.py
index 161410e..35abd7d 100644
--- a/backend/src/ely_eye/asr.py
+++ b/backend/src/ely_eye/asr.py
@@ -115,7 +115,7 @@ def _segment(segment: Any) -> SpeechSegment:
 
 
 class SpeechTranscriber:
-    """Whisper on CTranslate2: 88.9 seconds of speech in 1.7 seconds of CPU int8 (bench/reports/ASR.md)."""
+    """Whisper on CTranslate2, greedy on CPU int8; bench/reports/ASR.md carries the measured speed."""
 
     def __init__(self, settings: Settings | None = None) -> None:
         self.settings = settings or get_settings()
diff --git a/bench/asr_check.py b/bench/asr_check.py
index 741435f..b5ab4dd 100644
--- a/bench/asr_check.py
+++ b/bench/asr_check.py
@@ -148,11 +148,20 @@ def speech_atoms_in_the_store(videos: list[Path]) -> dict[str, Any]:
             service.ingest_path(video)
         atoms = database.list_atoms()
         audio = [atom for atom in atoms if atom.modality == Modality.audio]
+        out_of_order = 0
+        before_their_segment = 0
+        for atom in audio:
+            segment_start = float(atom.metadata.get("start_seconds", 0.0))
+            starts = [float(word["start"]) for word in atom.metadata.get("words", [])]
+            out_of_order += sum(1 for first, second in pairwise(starts) if second < first)
+            before_their_segment += sum(1 for start in starts if start < segment_start - 0.01)
         return {
             "atoms_all": len(atoms),
             "speech_atoms": len(audio),
             "word_timestamps": sum(len(atom.metadata.get("words", [])) for atom in audio),
             "sources": len({atom.source_id for atom in audio}),
+            "out_of_order_in_store": out_of_order,
+            "before_their_segment_in_store": before_their_segment,
         }
 
 
@@ -265,8 +274,9 @@ def write_markdown(report: dict[str, Any]) -> None:
         (
             f"Ingested through the product path, the store holds {totals['speech_atoms']} audio atoms from "
             f"{totals['sources']} sources carrying {totals['word_timestamps']} word timestamps "
-            f"({totals['out_of_order']} out of order, {totals['before_their_segment']} before their own segment) "
-            f"out of {totals['atoms_all']} atoms in total."
+            f"({totals['out_of_order_in_store']} out of order, "
+            f"{totals['before_their_segment_in_store']} before their own segment) out of {totals['atoms_all']} "
+            "atoms in total, checked on the words as stored rather than on the model's answer."
         ),
         "",
         (