transcribe: scope missing_spans to the unmatched audio itself, not the whole vocal section

Also fix a secondary ripple in build_notes(): a skipped row (inside a
missing span) no longer advances prev_line/prev_end, so it can't corrupt
line-initial spacing or break timing for its own line's later words.

src/songtrace/notes.py

@@ -84,14 +84,20 @@ def build_notes(rows: list[dict], times, f0, conf, language: str | None,
                 ) -> tuple[list[TimedNote], list[float], list[str]]:
     notes: list[TimedNote] = []
     breaks: list[float] = []
-    prev_line, prev_end = None, 0.0
+    prev_line, prev_end, last_seen_line = None, 0.0, None
     for row in rows:
-        if prev_line is not None and row["line_index"] > prev_line:
+        # last_seen_line tracks every row (skipped or not) so a run of
+        # skipped rows can't trigger a duplicate break on the next row of
+        # the same still-unseen line; prev_line/prev_end only advance on
+        # rows that actually emit notes, so a skipped row can't corrupt
+        # line_initial or break timing for its own line's later words.
+        if last_seen_line is not None and row["line_index"] > last_seen_line:
             breaks.append((prev_end + row["start"]) / 2)
+        last_seen_line = row["line_index"]
         line_initial = row["line_index"] != prev_line
-        prev_line, prev_end = row["line_index"], row["end"]
         if any(a <= row["start"] < b for a, b in missing_spans):
             continue
+        prev_line, prev_end = row["line_index"], row["end"]
         segs = segment_span(times, f0, conf, row["start"], row["end"])
         if not segs:
             pitch = notes[-1].pitch if notes else 0

src/songtrace/stages/align.py

@@ -106,7 +106,7 @@ def _run(ctx: Ctx) -> None:
             "wrong lyrics or wrong recording?")
     # normalised so an inverted span can never collapse a section onto one instant
     sections = [(min(a, b), max(a, b)) for a, b in vocal_sections(segments)]
-    dropped_lines, missing_spans = classify_lyrics_match(segments, ref, sections)
+    dropped_lines, missing_spans = classify_lyrics_match(segments, ref)
     matched = [i for i in range(len(ref.lines)) if i not in set(dropped_lines)]
     vocals = ctx.work / "vocals.wav"
     rows = []

src/songtrace/stages/transcribe.py

@@ -39,14 +39,17 @@ def lyrics_similarity(segments, ref: RefLyrics) -> float:
     return matcher.ratio()
 
 
-def classify_lyrics_match(segments, ref: RefLyrics, sections
+def classify_lyrics_match(segments, ref: RefLyrics, pad: float = 1.0
                           ) -> tuple[list[int], list[tuple[float, float]]]:
     """Split reference lines into matched vs. dropped, and flag sung spans no
     reference line explains.
 
     dropped_lines: reference line indices covered only by 'insert' opcodes
-    (present in the lyrics, never heard). missing_spans: vocal `sections`
-    containing 'delete' opcodes (heard, but matching no reference word).
+    (present in the lyrics, never heard). missing_spans: the padded, merged
+    bounds of the heard segments behind 'delete' opcodes (heard, but matching
+    no reference word) — scoped tightly to the unmatched audio itself, not
+    the whole vocal section it falls in, so matched lines sharing a section
+    with an ad-lib keep their notes.
     """
     matcher, seg_of, line_of = match_lyrics(segments, ref)
     covered = [False] * len(line_of)
@@ -59,17 +62,25 @@ def classify_lyrics_match(segments, ref: RefLyrics, sections
         by_line.setdefault(li, []).append(covered[j])
     dropped_lines = sorted(li for li, cov in by_line.items() if not any(cov))
 
-    missing = set()
+    spans = []
     for tag, ai1, ai2, _, _ in matcher.get_opcodes():
         if tag != "delete":
             continue
-        si = seg_of[ai1]
-        mid = (segments[si].start + segments[si].end) / 2
-        for a, b in sections:
-            if a <= mid <= b:
-                missing.add((a, b))
-                break
-    return dropped_lines, sorted(missing)
+        sis = [seg_of[i] for i in range(ai1, ai2)]
+        start = max(0.0, min(segments[si].start for si in sis) - pad)
+        end = max(segments[si].end for si in sis) + pad
+        spans.append((start, end))
+    return dropped_lines, _merge_spans(spans)
+
+
+def _merge_spans(spans: list[tuple[float, float]]) -> list[tuple[float, float]]:
+    merged: list[list[float]] = []
+    for a, b in sorted(spans):
+        if merged and a <= merged[-1][1]:
+            merged[-1][1] = max(merged[-1][1], b)
+        else:
+            merged.append([a, b])
+    return [tuple(s) for s in merged]
 
 
 def _run(ctx: Ctx) -> None:

tests/test_notes.py

@@ -325,6 +325,23 @@ def test_warnings_report_missing_spans():
     assert warnings == ["missing lyrics near 1:21–1:29"]
 
 
+def test_build_notes_skipped_row_mid_line_does_not_corrupt_spacing_or_breaks():
+    # "gone" falls inside a missing span and is skipped; "away" is the same
+    # line's next word and must still get its leading space, and the break
+    # before the next line must use the last *emitted* word's end (3.4, from
+    # "away"), not the skipped row's end (2.4).
+    times, f0, conf = flat_pitch()
+    rows = [
+        {"word": "keep", "start": 1.0, "end": 1.4, "score": 0.9, "line_index": 0},
+        {"word": "gone", "start": 2.0, "end": 2.4, "score": 0.9, "line_index": 0},
+        {"word": "away", "start": 3.0, "end": 3.4, "score": 0.9, "line_index": 0},
+        {"word": "next", "start": 5.0, "end": 5.4, "score": 0.9, "line_index": 1},
+    ]
+    notes, breaks, _ = build_notes(rows, times, f0, conf, "English",
+                                   missing_spans=[(1.9, 2.5)])
+    assert [n.text for n in notes] == ["keep", " away", "next"]
+    assert breaks == [(3.4 + 5.0) / 2]
+
 def test_notes_carry_line_index():
     times, f0, conf = flat_pitch()
     rows = [{"word": "hey", "start": 1.0, "end": 1.4, "score": 0.9, "line_index": 3}]

tests/test_transcribe.py

@@ -30,8 +30,7 @@ def test_similarity_low_for_wrong_lyrics():
 def test_classify_lyrics_match_flags_extra_reference_line():
     ref = normalize_lyrics("she's got a smile\nthat it seems to me\nbut then it fades")
     segs = [seg(1, 4, "she's got a smile that it seems to me")]
-    sections = vocal_sections(segs)
-    dropped, missing = classify_lyrics_match(segs, ref, sections)
+    dropped, missing = classify_lyrics_match(segs, ref)
     assert dropped == [2]
     assert missing == []
 
@@ -39,8 +38,7 @@ def test_classify_lyrics_match_flags_unmatched_singing():
     ref = normalize_lyrics("she's got a smile\nthat it seems to me")
     segs = [seg(1, 4, "she's got a smile that it seems to me"),
             seg(20, 23, "completely unrelated ad lib bridge")]
-    sections = vocal_sections(segs)
-    dropped, missing = classify_lyrics_match(segs, ref, sections)
+    dropped, missing = classify_lyrics_match(segs, ref)
     assert dropped == []
     assert missing == [(19.0, 24.0)]
 
@@ -49,6 +47,20 @@ def test_classify_lyrics_match_keeps_partially_matched_lines():
     # line 1 heard with one word garbled ("it" -> "bit"): still a replace/equal
     # match, so the line stays matched rather than dropped
     segs = [seg(1, 4, "she's got a smile that bit seems to me")]
-    sections = vocal_sections(segs)
-    dropped, _ = classify_lyrics_match(segs, ref, sections)
+    dropped, _ = classify_lyrics_match(segs, ref)
     assert dropped == []
+
+def test_classify_lyrics_match_scopes_missing_span_to_adlib_not_whole_section():
+    # matched line and an unmatched ad-lib close enough together that
+    # vocal_sections would merge them into one section; missing_spans must
+    # stay tight around the ad-lib so the matched line keeps its notes.
+    ref = normalize_lyrics("she's got a smile\nthat it seems to me")
+    segs = [seg(1, 4, "she's got a smile that it seems to me"),
+            seg(6, 8, "completely unrelated ad lib")]
+    sections = vocal_sections(segs)
+    assert sections == [(0.0, 9.0)]      # confirms the two segments do merge
+    dropped, missing = classify_lyrics_match(segs, ref)
+    assert dropped == []
+    assert missing == [(5.0, 9.0)]
+    for a, b in missing:
+        assert not (a <= 1.0 < b)        # matched line's start (1.0) untouched