conductor(score_dynamics_giorgini): Phase 1 Acquire - transcript (1485 clean segments, 46.5KB) + 178MB mp4

conductor/tracks/video_analysis_score_dynamics_giorgini_20260621/artifacts/phase1.log

@@ -0,0 +1,9 @@
+Phase 1 Acquire for score_dynamics_giorgini: https://youtu.be/P75iVMmbqQk
+Artifacts: C:\projects\manual_slop\conductor\tracks\video_analysis_score_dynamics_giorgini_20260621\artifacts
+Step 1: extract_transcript (yt-dlp VTT directly)
+  OK: wrote C:\projects\manual_slop\conductor\tracks\video_analysis_score_dynamics_giorgini_20260621\artifacts\transcript.json (2998 segments)
+Step 2: download_video
+{
+  "status": "error",
+  "error": "download_video: YtdlpError: ERROR: unable to download video data: HTTP Error 403: Forbidden\n"
+}

conductor/tracks/video_analysis_score_dynamics_giorgini_20260621/artifacts/video.log

@@ -0,0 +1,17 @@
+# yt-dlp log
+# url: https://youtu.be/P75iVMmbqQk
+# output: conductor/tracks/video_analysis_score_dynamics_giorgini_20260621/artifacts/video.mp4
+# returncode: 0
+
+stdout:
+[youtube] Extracting URL: https://youtu.be/P75iVMmbqQk
+[youtube] P75iVMmbqQk: Downloading webpage
+WARNING: [youtube] No supported JavaScript runtime could be found. Only deno is enabled by default.
+[youtube] P75iVMmbqQk: Downloading android vr player API JSON
+[info] P75iVMmbqQk: Downloading 1 format(s): 400+251
+[download] video.mp4.f400.mp4 (125.41MiB)
+[download] video.mp4.f251.webm (52.64MiB)
+[Merger] Merging formats into video.mp4 (Matroska / WebM container)
+
+stderr:
+WARNING: yt-dlp EJS not enabled; some formats may be missing.

scripts/tier2/artifacts/video_analysis_campaign_20260621/clean_transcript.py

@@ -0,0 +1,95 @@
+"""Clean yt-dlp auto-sub VTT transcripts.
+
+yt-dlp auto-subs produce rolling captions where each segment extends the
+previous one with new words, sometimes triplicated. Algorithm:
+  1. Strip VTT tags (<00:00:00.560><c>...</c>) from raw text.
+  2. For each pair (prev, curr), compute the new suffix curr adds vs prev.
+     Keep only the new suffix.
+  3. Drop empty / duplicate results.
+  4. Skip segments that are pure repetition of the prior segment.
+"""
+import json
+import re
+from pathlib import Path
+
+VTT_TAG = re.compile(r"<[^>]+>")
+WS = re.compile(r"\s+")
+
+def strip_vtt(t: str) -> str:
+    return WS.sub(" ", VTT_TAG.sub("", t)).strip()
+
+def longest_common_prefix_len(a: str, b: str) -> int:
+    n = min(len(a), len(b))
+    i = 0
+    while i < n and a[i] == b[i]:
+        i += 1
+    return i
+
+def longest_common_suffix_len(a: str, b: str, max_k: int = 80) -> int:
+    n = min(len(a), len(b), max_k)
+    i = 0
+    while i < n and a[-1 - i] == b[-1 - i]:
+        i += 1
+    return i
+
+def main(track: str) -> None:
+    art = Path(f"conductor/tracks/{track}/artifacts")
+    p = art / "transcript.json"
+    data = json.loads(p.read_text(encoding="utf-8"))
+    raw_segments = data["segments"]
+
+    cleaned: list[dict] = []
+    prev_clean = ""
+    for raw in raw_segments:
+        text = strip_vtt(raw["text"])
+        if not text:
+            continue
+        if prev_clean and text == prev_clean:
+            continue
+        if prev_clean and text.startswith(prev_clean):
+            new = text[len(prev_clean):].strip()
+            if not new:
+                continue
+            cleaned.append({"start": raw["start"], "text": new})
+            prev_clean = text
+            continue
+        lcp = longest_common_prefix_len(prev_clean, text)
+        if lcp >= 5:
+            new = text[lcp:].strip()
+            if new:
+                cleaned.append({"start": raw["start"], "text": new})
+                prev_clean = text
+                continue
+        lcs = longest_common_suffix_len(prev_clean, text)
+        if lcs >= 5:
+            new = text[: -lcs if lcs < len(text) else 0].strip()
+            if new:
+                cleaned.append({"start": raw["start"], "text": new})
+                prev_clean = text
+                continue
+        cleaned.append({"start": raw["start"], "text": text})
+        prev_clean = text
+
+    deduped: list[dict] = []
+    seen: set[str] = set()
+    for seg in cleaned:
+        t = seg["text"]
+        if t in seen:
+            continue
+        seen.add(t)
+        deduped.append(seg)
+
+    plain = "\n".join(s["text"] for s in deduped)
+    (art / "transcript_clean.txt").write_text(plain, encoding="utf-8")
+    data["clean_segments"] = deduped
+    data["plain"] = plain
+    p.write_text(json.dumps(data, indent=2, ensure_ascii=False), encoding="utf-8")
+    print(f"{track}: {len(raw_segments)} raw -> {len(cleaned)} cleaned -> {len(deduped)} deduped")
+    print(f"plain length: {len(plain)} chars")
+    print("First 800 chars:")
+    print(plain[:800])
+
+
+if __name__ == "__main__":
+    import sys
+    main(sys.argv[1] if len(sys.argv) > 1 else "video_analysis_score_dynamics_giorgini_20260621")