feat(legendas): sub-frases por vírgula e empacotamento em compound clip

split_into_subphrases divide a frase na vírgula — onde a fala respira —
mas funde de volta o pedaço curto ("né?", "Então..."), que lê como parte
da frase anterior e não como bloco próprio.

wrap_titles_in_compound empacota os títulos de uma sub-frase num compound
clip, replicando a estrutura que o próprio Final Cut produz: o primeiro
título vira âncora do spine em offset 0, os demais penduram nele por lane,
e um ref-clip toma o lugar deles na lane original. Os offsets dos filhos
são rebaseados para o espaço de tempo da âncora, senão cada palavra
escorregaria pela diferença entre os dois start.

Junto: _filter_children_for_segment passa a filtrar também o <video> do
Clipe de Ajuste. Sem isso, cada corte subsequente duplicava o zoom em
todos os pedaços resultantes com o offset original intacto, e as cópias
desenhavam empilhadas na mesma posição da timeline.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

code/fcpxml/transcribe.py

@@ -316,6 +316,54 @@ def group_words_by_segment(
     return groups
 
 
+def split_into_subphrases(
+    words: Sequence[dict],
+    min_words: int = 3,
+) -> List[List[dict]]:
+    """Split a sentence's *words* into sub-phrases at comma boundaries.
+
+    A comma is where a spoken sentence actually breathes, so it is the
+    natural seam for grouping subtitles — each sub-phrase becoming its own
+    on-screen block (and, downstream, its own compound clip).
+
+    The exception is the short tail: a fragment like "né?" or "Então..."
+    reads as part of the phrase before it, not as a phrase of its own, and
+    promoting it to its own block would flash a single word on screen. So a
+    piece shorter than *min_words* is merged back into its neighbour —
+    preferring the previous piece, falling back to the next one when the
+    short piece leads the sentence.
+
+    Returns one group per sub-phrase; a sentence with no comma comes back
+    as a single group.
+    """
+    pieces: List[List[dict]] = []
+    current: List[dict] = []
+    for w in words:
+        current.append(w)
+        text = str(w.get('word') or w.get('text') or '')
+        if text.rstrip().endswith(','):
+            pieces.append(current)
+            current = []
+    if current:
+        pieces.append(current)
+
+    if len(pieces) <= 1:
+        return pieces
+
+    merged: List[List[dict]] = []
+    for piece in pieces:
+        if len(piece) < min_words and merged:
+            merged[-1].extend(piece)
+        else:
+            merged.append(piece)
+    # A short leading piece has no previous neighbour to fold into, so it
+    # folds forward instead.
+    if len(merged) > 1 and len(merged[0]) < min_words:
+        merged[1][:0] = merged[0]
+        merged.pop(0)
+    return merged
+
+
 def segments_to_srt(segments: Sequence[dict]) -> str:
     """Render transcript segments as an SRT string (for captions import)."""