refactor(verification): import path delegates to shared core
verify_audio_file now calls audio_verification.evaluate() and re-exports normalize/similarity/_alias_aware_artist_sim from the core, so import and the library scan can no longer drift apart. Alias-rescue diagnostic moved to the core. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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3 changed files with 62 additions and 392 deletions
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@ -56,166 +56,29 @@ class VerificationResult(Enum):
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ERROR = "error" # Lookup errored (invalid key / rate limit / no backend) - continue, but flag it
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ERROR = "error" # Lookup errored (invalid key / rate limit / no backend) - continue, but flag it
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def _normalize(text: str) -> str:
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# normalize() + similarity() + the alias-aware comparison now live in the shared
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"""Normalize a string for comparison: lowercase, strip parentheticals, punctuation."""
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# decision core (core/matching/audio_verification.py) so import-time verification
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if not text:
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# and the library scan share ONE definition — the <>-strip fix, CJK handling and
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return ""
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# thresholds can't drift apart again. Names kept (`_normalize` etc.) for existing
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s = text.lower().strip()
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# importers/tests.
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# Remove ALL parenthetical suffixes — these are metadata annotations, not core title
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from core.matching.audio_verification import ( # noqa: E402
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# Covers: (Live), (Remastered), (Parody of ...), (from "..." Soundtrack), (feat. ...), etc.
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normalize as _normalize,
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s = re.sub(r'\s*\([^)]*\)', '', s)
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similarity as _similarity,
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# Remove ALL square bracket suffixes: [Live], [Remastered], [Deluxe], etc.
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_alias_aware_artist_sim,
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s = re.sub(r'\s*\[[^\]]*\]', '', s)
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_find_best_title_artist_match as _core_find_best_title_artist_match,
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# Remove trailing featuring info not in parentheses: "feat. ...", "ft. ...", "featuring ..."
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evaluate as _core_evaluate,
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s = re.sub(r'\s+(?:feat\.?|ft\.?|featuring)\s+.*$', '', s, flags=re.IGNORECASE)
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Decision as _CoreDecision,
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# Remove dash-separated version tags: "- Vocal", "- Instrumental", "- Acoustic", etc.
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)
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s = re.sub(r'\s*-\s*(?:vocal|instrumental|acoustic|live|remix|cover|clean|explicit|radio\s*edit|original\s*mix|extended\s*mix|club\s*mix)\s*$', '', s, flags=re.IGNORECASE)
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# Remove soundtrack/source subtitles: ' - From "..." Soundtrack', ' - from the film ...'
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s = re.sub(r'\s*-\s*from\s+.+$', '', s, flags=re.IGNORECASE)
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# Remove non-alphanumeric except spaces
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s = re.sub(r'[^\w\s]', '', s)
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# Collapse whitespace
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s = re.sub(r'\s+', ' ', s).strip()
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return s
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def _similarity(a: str, b: str) -> float:
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def _find_best_title_artist_match(recordings, expected_title, expected_artist,
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"""Calculate similarity between two strings (0.0-1.0) after normalization."""
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expected_artist_aliases=None):
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na = _normalize(a)
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"""Back-compat wrapper around the shared core matcher (keeps the
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nb = _normalize(b)
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``expected_artist_aliases`` kwarg name for existing callers/tests)."""
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if not na or not nb:
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return _core_find_best_title_artist_match(
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return 0.0
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recordings, expected_title, expected_artist, expected_artist_aliases,
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if na == nb:
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return 1.0
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return SequenceMatcher(None, na, nb).ratio()
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def _alias_aware_artist_sim(
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expected_artist: str,
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actual_artist: str,
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aliases: Optional[Any] = None,
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) -> float:
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"""Best artist-similarity across (expected, *aliases) vs actual.
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Issue #442 — when expected and actual are in different scripts
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(e.g. `Hiroyuki Sawano` vs `澤野弘之`), raw `_similarity` scores
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near 0% even though MusicBrainz aliases bridge them. Routes
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through the pure helper so the verifier inherits one shared
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contract.
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Returns the highest score across all candidates so existing
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threshold checks (>= ARTIST_MATCH_THRESHOLD) keep their
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semantics. When `aliases` is None or empty, behaves identically
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to the prior raw `_similarity(expected, actual)` call.
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`aliases` accepts two shapes:
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- **Iterable** (list/tuple/set of strings): used directly. Used
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by tests that already know the aliases.
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- **Callable**: invoked LAZILY only when direct similarity
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falls below the threshold. Lets the verifier pass a memoizing
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thunk that resolves aliases (DB / cache / live MB) only when
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needed. Verifications where the direct match already passes
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never trigger the lookup chain — no wasted DB query for the
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happy path.
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Diagnostic logging: emits an INFO line whenever an alias rescues
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a comparison that direct similarity would have failed. Lets
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future bug reports trace which alias triggered which PASS
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decision (e.g. "this file passed because alias `澤野弘之` matched
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the file's artist tag").
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"""
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from core.matching.artist_aliases import artist_names_match
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direct = _similarity(expected_artist, actual_artist)
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# Fast path — direct match already passes the threshold OR caller
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# supplied no aliases handle. Avoids any lookup work.
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if aliases is None:
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return direct
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if direct >= ARTIST_MATCH_THRESHOLD:
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return direct
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# Resolve the iterable. Callable provider invoked NOW (lazily —
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# the caller can memoize the result across multiple invocations
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# within one verify_audio_file call).
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resolved = aliases() if callable(aliases) else aliases
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if not resolved:
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return direct
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_matched, score = artist_names_match(
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expected_artist,
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actual_artist,
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aliases=resolved,
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threshold=ARTIST_MATCH_THRESHOLD,
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similarity=_similarity,
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)
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)
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# Diagnostic — alias rescued a comparison that direct would
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# have failed. Worth logging at INFO since it's a user-visible
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# decision (file PASS instead of FAIL). One line per rescue
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# within a single verify call.
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if score >= ARTIST_MATCH_THRESHOLD and direct < ARTIST_MATCH_THRESHOLD:
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from core.matching.artist_aliases import best_alias_match
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winner, _ = best_alias_match(
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expected_artist, actual_artist, resolved, similarity=_similarity,
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)
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logger.info(
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"Artist alias rescued comparison: expected=%r vs actual=%r "
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"(direct sim=%.2f, alias %r → score=%.2f)",
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expected_artist, actual_artist, direct, winner, score,
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)
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return score
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def _find_best_title_artist_match(
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recordings: List[Dict[str, Any]],
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expected_title: str,
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expected_artist: str,
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expected_artist_aliases: Optional[Any] = None,
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) -> Tuple[Optional[Dict], float, float]:
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"""
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Find the AcoustID recording that best matches expected title/artist.
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Issue #442 — `expected_artist_aliases` (when supplied) is the
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list of alternate spellings for `expected_artist` (Japanese
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kanji, Cyrillic, etc.). Accepts either:
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- An iterable of alias strings (used eagerly), or
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- A callable returning the list (resolved lazily — only fires
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when at least one recording fails direct artist similarity).
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Each recording's artist is scored against (expected, *aliases)
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and the best score wins. When the list is empty/omitted/None,
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behavior is identical to the prior raw similarity comparison.
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Returns:
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(best_recording, title_similarity, artist_similarity)
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"""
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best_rec = None
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best_title_sim = 0.0
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best_artist_sim = 0.0
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best_combined = 0.0
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for rec in recordings:
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title = rec.get('title') or ''
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artist = rec.get('artist') or ''
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title_sim = _similarity(expected_title, title)
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artist_sim = _alias_aware_artist_sim(
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expected_artist, artist, expected_artist_aliases,
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)
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# Weight title higher since that's the primary identifier
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combined = (title_sim * 0.6) + (artist_sim * 0.4)
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if combined > best_combined:
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best_combined = combined
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best_rec = rec
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best_title_sim = title_sim
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best_artist_sim = artist_sim
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return best_rec, best_title_sim, best_artist_sim
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# Shared MusicBrainz client for enrichment lookups
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# Shared MusicBrainz client for enrichment lookups
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_mb_client = None
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_mb_client = None
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@ -466,241 +329,32 @@ class AcoustIDVerification:
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)
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)
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return _alias_cache['value']
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return _alias_cache['value']
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# Step 4: Find best title/artist match among AcoustID results
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# Steps 4-5: delegate the PASS/SKIP/FAIL decision to the shared core
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best_rec, title_sim, artist_sim = _find_best_title_artist_match(
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# (core/matching/audio_verification.evaluate) so import verification
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recordings, expected_track_name, expected_artist_name,
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# and the library scan apply identical logic.
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expected_artist_aliases=_aliases_provider,
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outcome = _core_evaluate(
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expected_track_name, expected_artist_name, recordings,
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fingerprint_score=best_score,
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aliases_provider=_aliases_provider,
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)
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)
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if not best_rec:
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return VerificationResult.SKIP, "No recordings with title/artist info"
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matched_title = best_rec.get('title', '?')
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matched_artist = best_rec.get('artist', '?')
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logger.info(
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logger.info(
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f"Best match: '{matched_title}' by '{matched_artist}' "
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"Best match: '%s' by '%s' (title_sim=%.2f, artist_sim=%.2f) -> %s",
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f"(title_sim={title_sim:.2f}, artist_sim={artist_sim:.2f})"
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outcome.matched_title, outcome.matched_artist,
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outcome.title_sim, outcome.artist_sim, outcome.decision.value,
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)
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)
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_decision_map = {
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# Step 4b: Version-mismatch gate.
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_CoreDecision.PASS: VerificationResult.PASS,
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#
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_CoreDecision.SKIP: VerificationResult.SKIP,
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# The ``_normalize`` step deliberately strips parentheticals and
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_CoreDecision.FAIL: VerificationResult.FAIL,
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# version tags ("(Instrumental)", "- Live", etc) so that legit
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}
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# name variations don't fail the title-similarity comparison.
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result = _decision_map[outcome.decision]
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# That same stripping made it impossible to tell a vocal track
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if result == VerificationResult.PASS:
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# apart from its instrumental: "In My Feelings" and "In My
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logger.info("AcoustID verification PASSED - %s", outcome.reason)
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# Feelings (Instrumental)" both normalize to "in my feelings",
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elif result == VerificationResult.FAIL:
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# the title sim ends up 1.0, and the file passes verification
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logger.warning("AcoustID verification FAILED - %s", outcome.reason)
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# even though it's the wrong cut.
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else:
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#
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logger.info("AcoustID verification SKIPPED - %s", outcome.reason)
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# Detect the version on each side BEFORE normalization runs.
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return result, outcome.reason
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# If the expected track and the AcoustID-matched recording
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# disagree on version (one is original, the other is
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# instrumental / live / remix / acoustic / etc), reject — the
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# fingerprint identified a real song but it's not the one the
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# caller asked for.
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expected_version = _detect_title_version(expected_track_name)
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matched_version = _detect_title_version(matched_title)
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if expected_version != matched_version:
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# Issue #607 (AfonsoG6): MusicBrainz often stores live
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# recordings with bare titles ("Clarity") while the
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# release entry carries the venue annotation ("Clarity
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# (Live at Blossom Music Center, ...)"). The fingerprint
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# correctly identifies the LIVE recording; only the
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# title text is bare. Helper accepts the one-sided bare
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# case when fingerprint + bare-title + artist all agree.
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# Two-sided version mismatches (live vs remix etc) stay
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# strict — those are genuinely different recordings.
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if is_acceptable_version_mismatch(
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expected_version, matched_version,
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fingerprint_score=best_score,
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title_similarity=title_sim,
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artist_similarity=artist_sim,
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):
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logger.info(
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f"AcoustID version annotation differs (expected={expected_version}, "
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f"matched={matched_version}) but fingerprint+title+artist all match — "
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f"accepting (likely MB metadata gap on a live/version-annotated recording)"
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)
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else:
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msg = (
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f"Version mismatch: expected '{expected_track_name}' ({expected_version}) "
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f"but file is '{matched_title}' ({matched_version})"
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)
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logger.warning(f"AcoustID verification FAILED (version mismatch) - {msg}")
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return VerificationResult.FAIL, msg
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# Step 5: Decide pass/fail based on similarity
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if title_sim >= TITLE_MATCH_THRESHOLD and artist_sim >= ARTIST_MATCH_THRESHOLD:
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msg = (
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f"Audio verified: '{matched_title}' by '{matched_artist}' "
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f"matches expected '{expected_track_name}' by '{expected_artist_name}' "
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f"(title={title_sim:.0%}, artist={artist_sim:.0%})"
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)
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logger.info(f"AcoustID verification PASSED - {msg}")
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return VerificationResult.PASS, msg
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# Title matches but artist doesn't — could be a cover/collab OR a
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# genuinely different track with the same name. Distinguish the
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# two by checking whether the expected artist appears anywhere in
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# AcoustID's returned recordings.
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if title_sim >= TITLE_MATCH_THRESHOLD and artist_sim < ARTIST_MATCH_THRESHOLD:
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# First: if the expected artist is present in ANY recording's
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# metadata for this fingerprint, it's likely the right track
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# (AcoustID's "best" match just picked the wrong variant).
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for rec in recordings:
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rec_artist = rec.get('artist', '')
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if _alias_aware_artist_sim(
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expected_artist_name, rec_artist, _aliases_provider,
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) >= ARTIST_MATCH_THRESHOLD:
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msg = (
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f"Audio verified: found '{expected_track_name}' by '{expected_artist_name}' "
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f"in AcoustID results"
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)
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logger.info(f"AcoustID verification PASSED (secondary match) - {msg}")
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return VerificationResult.PASS, msg
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# Expected artist wasn't found anywhere. Decide between:
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# - FAIL: clear mismatch, e.g. "Tom Walker" (sim ~0.2) when
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# expecting "Maduk" — different song with same name
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# - SKIP: ambiguous, e.g. collab / alt credit / formatting
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# difference (sim 0.3-0.6)
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#
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# The 0.3 cutoff catches hard mismatches while preserving the
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# benefit of the doubt for borderline artist formatting.
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CLEAR_MISMATCH_THRESHOLD = 0.3
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if artist_sim < CLEAR_MISMATCH_THRESHOLD:
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msg = (
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f"Audio mismatch: file identified as '{matched_title}' by '{matched_artist}', "
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f"expected '{expected_track_name}' by '{expected_artist_name}' "
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f"(title={title_sim:.0%}, artist={artist_sim:.0%}) — "
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f"expected artist not found in any AcoustID recording"
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)
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logger.warning(f"AcoustID verification FAILED (clear artist mismatch) - {msg}")
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return VerificationResult.FAIL, msg
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msg = (
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f"Title matches but artist unclear: "
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f"AcoustID='{matched_title}' by '{matched_artist}', "
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f"expected '{expected_track_name}' by '{expected_artist_name}' "
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f"(artist_sim={artist_sim:.0%} — ambiguous, could be cover/collab)"
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)
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logger.info(f"AcoustID verification SKIPPED - {msg}")
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return VerificationResult.SKIP, msg
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# Title doesn't match — check ALL recordings for any title/artist match
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# (the best combined match might not be the right one if there are many results)
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# Skip recordings whose version (instrumental/live/etc) disagrees with
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# what the caller asked for — the version mismatch above checked
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# only the best recording, but a wrong-version variant could still
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# win this fallback scan if its bare title matched.
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for rec in recordings:
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t = rec.get('title') or ''
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a = rec.get('artist') or ''
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if _detect_title_version(t) != expected_version:
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continue
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if (_similarity(expected_track_name, t) >= TITLE_MATCH_THRESHOLD and
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_alias_aware_artist_sim(
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expected_artist_name, a, _aliases_provider,
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) >= ARTIST_MATCH_THRESHOLD):
|
|
||||||
msg = (
|
|
||||||
f"Audio verified: found '{t}' by '{a}' in AcoustID results "
|
|
||||||
f"matching expected '{expected_track_name}' by '{expected_artist_name}'"
|
|
||||||
)
|
|
||||||
logger.info(f"AcoustID verification PASSED (scan match) - {msg}")
|
|
||||||
return VerificationResult.PASS, msg
|
|
||||||
|
|
||||||
# No match found — but if fingerprint score is very high (≥0.95)
|
|
||||||
# AND we have evidence the mismatch is a language/script case
|
|
||||||
# (rather than two genuinely different songs by the same artist),
|
|
||||||
# skip rather than quarantine a correct file. Two routes:
|
|
||||||
#
|
|
||||||
# (a) Either side of the comparison contains non-ASCII characters
|
|
||||||
# — strong signal of transliteration / kanji↔roman cases.
|
|
||||||
# Artist must still be a strong match to use this path.
|
|
||||||
# (b) Both title AND artist similarity are very high (the song
|
|
||||||
# is recognizably the same with minor punctuation / casing
|
|
||||||
# differences that fell below the strict match thresholds).
|
|
||||||
#
|
|
||||||
# The OLD logic was ``title_sim >= 0.55 OR artist_sim >= match``.
|
|
||||||
# That fired for English-vs-English songs by the same artist that
|
|
||||||
# share NO actual content — e.g. "R.O.T.C (Interlude)" by
|
|
||||||
# Kendrick Lamar getting accepted as "Rich (Interlude)" by
|
|
||||||
# Kendrick Lamar because the artist matched perfectly and
|
|
||||||
# "interlude" was shared in both titles. Reported by user when
|
|
||||||
# downloading Mr. Morale: three tracks (Rich Interlude, Savior
|
|
||||||
# Interlude, Savior) all received the wrong R.O.T.C audio file
|
|
||||||
# because of this leak.
|
|
||||||
# Use the BEST matching recording's strings here (not
|
|
||||||
# `recordings[0]`) so the failure message reports the same
|
|
||||||
# candidate the title/artist similarity scores came from.
|
|
||||||
# Issue #607 (AfonsoG6) example 1: the prior code mixed
|
|
||||||
# `recordings[0]`'s strings (which can be empty) with
|
|
||||||
# `best_rec`'s scores, producing nonsense reasons like
|
|
||||||
# "file identified as '' by '' (artist=100%)" when a later
|
|
||||||
# recording in the list scored well on artist.
|
|
||||||
display_title = matched_title or '?'
|
|
||||||
display_artist = matched_artist or '?'
|
|
||||||
has_non_ascii = (
|
|
||||||
any(ord(c) > 127 for c in (expected_track_name or ''))
|
|
||||||
or any(ord(c) > 127 for c in display_title)
|
|
||||||
)
|
|
||||||
language_script_skip = (
|
|
||||||
best_score >= 0.95
|
|
||||||
and has_non_ascii
|
|
||||||
and artist_sim >= ARTIST_MATCH_THRESHOLD
|
|
||||||
)
|
|
||||||
high_confidence_strong_match_skip = (
|
|
||||||
best_score >= 0.95
|
|
||||||
and title_sim >= 0.80
|
|
||||||
and artist_sim >= ARTIST_MATCH_THRESHOLD
|
|
||||||
)
|
|
||||||
# Issue #797 — the EXPECTED artist and the AcoustID-matched
|
|
||||||
# artist are written in different scripts (e.g. "Joe Hisaishi"
|
|
||||||
# vs "久石譲") yet the alias-aware comparison still confirmed
|
|
||||||
# them as the same artist (artist_sim >= threshold, bridged via
|
|
||||||
# MusicBrainz aliases). When the artist itself spans scripts the
|
|
||||||
# title almost always does too — and a romanized-vs-native title
|
|
||||||
# comparison is meaningless, so it can't be evidence the file is
|
|
||||||
# wrong. Trust the confirmed artist + the fingerprint (already
|
|
||||||
# >= MIN_ACOUSTID_SCORE to reach here) and SKIP rather than
|
|
||||||
# quarantine a correct download of a non-English artist.
|
|
||||||
#
|
|
||||||
# Deliberately narrow (the "tight" scope): keyed on the ARTIST
|
|
||||||
# spanning scripts AND being confirmed. A same-script artist
|
|
||||||
# with only a cross-script TITLE (romaji artist + kanji title)
|
|
||||||
# is NOT covered — that case keeps the stricter 0.95 floor
|
|
||||||
# above, preserving the #607 wrong-file protection.
|
|
||||||
cross_script_artist_skip = (
|
|
||||||
best_score >= MIN_ACOUSTID_SCORE
|
|
||||||
and artist_sim >= ARTIST_MATCH_THRESHOLD
|
|
||||||
and is_cross_script_mismatch(expected_artist_name, display_artist)
|
|
||||||
)
|
|
||||||
if (language_script_skip or high_confidence_strong_match_skip
|
|
||||||
or cross_script_artist_skip):
|
|
||||||
reason = (
|
|
||||||
"likely same song in different language/script"
|
|
||||||
if (language_script_skip or cross_script_artist_skip)
|
|
||||||
else "title/artist match within tolerance"
|
|
||||||
)
|
|
||||||
msg = (
|
|
||||||
f"Title/artist mismatch but fingerprint confidence very high ({best_score:.2f}): "
|
|
||||||
f"AcoustID='{display_title}' by '{display_artist}', "
|
|
||||||
f"expected '{expected_track_name}' by '{expected_artist_name}' — "
|
|
||||||
f"{reason}"
|
|
||||||
)
|
|
||||||
logger.info(f"AcoustID verification SKIPPED (high confidence) - {msg}")
|
|
||||||
return VerificationResult.SKIP, msg
|
|
||||||
|
|
||||||
# Low fingerprint score + no metadata match — file is likely wrong.
|
|
||||||
msg = (
|
|
||||||
f"Audio mismatch: file identified as '{display_title}' by '{display_artist}', "
|
|
||||||
f"expected '{expected_track_name}' by '{expected_artist_name}' "
|
|
||||||
f"(title={title_sim:.0%}, artist={artist_sim:.0%})"
|
|
||||||
)
|
|
||||||
logger.warning(f"AcoustID verification FAILED - {msg}")
|
|
||||||
return VerificationResult.FAIL, msg
|
|
||||||
|
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
# Any unexpected error -> SKIP (fail open)
|
# Any unexpected error -> SKIP (fail open)
|
||||||
|
|
|
||||||
|
|
@ -16,6 +16,10 @@ from difflib import SequenceMatcher
|
||||||
from enum import Enum
|
from enum import Enum
|
||||||
from typing import Any, List, Optional
|
from typing import Any, List, Optional
|
||||||
|
|
||||||
|
from utils.logging_config import get_logger
|
||||||
|
|
||||||
|
logger = get_logger("audio_verification")
|
||||||
|
|
||||||
# Thresholds — the single definition both paths share.
|
# Thresholds — the single definition both paths share.
|
||||||
MIN_ACOUSTID_SCORE = 0.80 # Minimum fingerprint score to trust a match.
|
MIN_ACOUSTID_SCORE = 0.80 # Minimum fingerprint score to trust a match.
|
||||||
TITLE_MATCH_THRESHOLD = 0.70 # Title similarity to consider a match.
|
TITLE_MATCH_THRESHOLD = 0.70 # Title similarity to consider a match.
|
||||||
|
|
@ -117,6 +121,18 @@ def _alias_aware_artist_sim(expected_artist: str, actual_artist: str,
|
||||||
expected_artist, actual_artist, aliases=resolved,
|
expected_artist, actual_artist, aliases=resolved,
|
||||||
threshold=ARTIST_MATCH_THRESHOLD, similarity=similarity,
|
threshold=ARTIST_MATCH_THRESHOLD, similarity=similarity,
|
||||||
)
|
)
|
||||||
|
# Diagnostic: an alias rescued a comparison direct similarity would have
|
||||||
|
# failed. INFO since it's a user-visible decision (PASS instead of FAIL).
|
||||||
|
if score >= ARTIST_MATCH_THRESHOLD and direct < ARTIST_MATCH_THRESHOLD:
|
||||||
|
from core.matching.artist_aliases import best_alias_match
|
||||||
|
winner, _ = best_alias_match(
|
||||||
|
expected_artist, actual_artist, resolved, similarity=similarity,
|
||||||
|
)
|
||||||
|
logger.info(
|
||||||
|
"Artist alias rescued comparison: expected=%r vs actual=%r "
|
||||||
|
"(direct sim=%.2f, alias %r → score=%.2f)",
|
||||||
|
expected_artist, actual_artist, direct, winner, score,
|
||||||
|
)
|
||||||
return score
|
return score
|
||||||
|
|
||||||
|
|
||||||
|
|
|
||||||
|
|
@ -431,10 +431,10 @@ class TestAliasRescueLogging:
|
||||||
records.append(record)
|
records.append(record)
|
||||||
|
|
||||||
handler = _ListHandler(level=_logging.INFO)
|
handler = _ListHandler(level=_logging.INFO)
|
||||||
# Logger name is `soulsync.acoustid.verification` per
|
# The alias-aware comparison now lives in the shared core
|
||||||
# `core.acoustid_verification`'s `get_logger("acoustid_verification")`
|
# (`core.matching.audio_verification`, logger `audio_verification`),
|
||||||
# — dot-separated, NOT underscored.
|
# which is where the rescue diagnostic is emitted.
|
||||||
verifier_logger = _logging.getLogger('soulsync.acoustid.verification')
|
verifier_logger = _logging.getLogger('soulsync.audio_verification')
|
||||||
verifier_logger.addHandler(handler)
|
verifier_logger.addHandler(handler)
|
||||||
prior_level = verifier_logger.level
|
prior_level = verifier_logger.level
|
||||||
verifier_logger.setLevel(_logging.INFO)
|
verifier_logger.setLevel(_logging.INFO)
|
||||||
|
|
|
||||||
Loading…
Reference in a new issue