diff --git a/vllm_plugin/asr_streaming.py b/vllm_plugin/asr_streaming.py
index c97412fc..7c4274a2 100644
--- a/vllm_plugin/asr_streaming.py
+++ b/vllm_plugin/asr_streaming.py
@@ -200,6 +200,34 @@ def load_audio_bytes(audio_bytes: bytes, target_sr: int) -> np.ndarray:
 # merged into one card, which is why this runs here and not per block.
 _REPEAT_TAG_RE = re.compile(r"(\[[^\[\]]*\])(?:\s*\1)+")
 
+# A decode loop -- the model failure behind issue #415, usually triggered by a
+# stretch of non-speech -- emits the same text chunk after chunk, which renders
+# as that clause repeated down the transcript. A run of REPEAT_LOOP_MIN or more
+# byte-identical consecutive chunks is that loop: a real audio window rarely
+# transcribes identically twice, let alone three times running. One or two
+# repeats stay, since they can be genuine speech.
+REPEAT_LOOP_MIN = 3
+
+
+def mute_looped_chunks(chunk_texts: List[str]) -> List[str]:
+    """Blank all but the first of each long run of identical consecutive chunks.
+
+    Blanking, not dropping: chunk k's timestamp is ``k * chunk_seconds``, so the
+    slots have to stay. An emptied chunk folds into the open segment exactly as a
+    silent one does, which is what keeps a loop from repeating across the cards.
+    """
+    out = list(chunk_texts)
+    i = 0
+    while i < len(out):
+        j = i + 1
+        while j < len(out) and out[j] == out[i]:
+            j += 1
+        if out[i].strip() and j - i >= REPEAT_LOOP_MIN:
+            for k in range(i + 1, j):
+                out[k] = ""
+        i = j
+    return out
+
 # A card is one paragraph, so the line breaks the model emits inside a block
 # fold to single spaces -- except between two CJK characters, where a space is
 # not a word separator and just leaves a visible gap.
@@ -230,6 +258,7 @@ def chunk_segments(chunk_texts: List[str],
     ``duration`` only ever clamps the tail. While a clip is still streaming its
     real duration is unknown, and the chunk count is what defines the timeline.
     """
+    chunk_texts = mute_looped_chunks(chunk_texts)
     advance = geometry.chunk_seconds
     segments: List[Dict] = []
     cur_start = 0.0
diff --git a/vllm_plugin/tests/test_asr_streaming_repeat.py b/vllm_plugin/tests/test_asr_streaming_repeat.py
new file mode 100644
index 00000000..fffcd52a
--- /dev/null
+++ b/vllm_plugin/tests/test_asr_streaming_repeat.py
@@ -0,0 +1,49 @@
+#!/usr/bin/env python3
+"""Regression test for issue #415: a decode loop repeats the same clause across
+chunks, and chunk_segments used to render every copy verbatim.
+
+Torch-free: imports asr_streaming directly (numpy only) the same way the demo
+does, so it runs without weights, a GPU, or a vLLM install. Run with:
+
+    python3 vllm_plugin/tests/test_asr_streaming_repeat.py
+"""
+import os
+import sys
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+import asr_streaming as a  # noqa: E402
+
+# Released streaming geometry: 15-frame chunk, 4-frame lookahead at 24 kHz.
+GEOMETRY = a.ChunkGeometry(
+    sample_rate=24000, frame_samples=3200, chunk_frames=15, lookahead_frames=4)
+
+CLAUSE = "the cat sat on the mat. "
+LOOP_CHUNKS = 8            # a stuck model emits the same clause every chunk
+EMPHASIS = "No. No. "      # two repeats: real speech, must survive
+
+
+def _content(chunk_texts):
+    segs = a.chunk_segments(chunk_texts, GEOMETRY)
+    return " ".join(seg["Content"] for seg in segs)
+
+
+def test_loop_collapses():
+    body = _content([f"Speaker 0: {CLAUSE}"] * LOOP_CHUNKS)
+    hits = body.count("the cat sat on the mat")
+    print(f"[loop] {LOOP_CHUNKS} looped chunks -> clause appears {hits}x: {body!r}")
+    assert hits == 1, f"decode loop still repeats the clause {hits}x (issue #415)"
+
+
+def test_emphasis_survives():
+    # A short genuine repeat is below the loop threshold and stays untouched.
+    body = _content([f"Speaker 0: {EMPHASIS}"])
+    hits = body.count("No")
+    print(f"[emphasis] genuine double repeat -> 'No' appears {hits}x: {body!r}")
+    assert hits == 2, f"conservative threshold ate real repetition: {body!r}"
+
+
+if __name__ == "__main__":
+    test_loop_collapses()
+    test_emphasis_survives()
+    print("PASS")