Freeze independent DTW speech timing diagnostic and startup provenance

tools/speech-eval/dtw_alignment.py

@@ -0,0 +1,47 @@
+"""Frozen DTW sentence point spans, independent of ordinary token intervals."""
+from token_alignment import BOUNDARY, TEXT_TOKEN_LIMIT
+
+POLICY = "dtw-token-sentences-v1;centisecond-points;first-last-point-span;exact-text;no-labels"
+
+
+def aligned_segments(document, offset_ms, duration_ms):
+    from run import segments
+    originals = segments(document, offset_ms, duration_ms)
+    raw_rows = [row for row in document["transcription"] if row["text"].strip()]
+    result = []
+    previous = 0
+    for index, (row, original) in enumerate(zip(raw_rows, originals)):
+        tokens = row.get("tokens")
+        if not isinstance(tokens, list) or not 0 < len(tokens) <= 4096:
+            raise ValueError("Missing or oversized DTW tokens")
+        accepted = []
+        for token in tokens:
+            token_id, text = token.get("id"), token.get("text")
+            if type(token_id) is not int or token_id < 0 or not isinstance(text, str):
+                raise ValueError("Invalid DTW token identity")
+            if token_id >= TEXT_TOKEN_LIMIT:
+                if not text.startswith("[_") or not text.endswith("]"):
+                    raise ValueError("Unrecognized special token")
+                continue
+            point = token.get("t_dtw")
+            if type(point) is not int or not 0 <= point * 10 <= duration_ms or point * 10 < previous:
+                raise ValueError("Missing, invalid or nonmonotonic DTW point")
+            previous = point * 10
+            accepted.append((text, previous))
+        if "".join(token[0] for token in accepted) != row["text"]:
+            raise ValueError("DTW text differs from original recognized segment")
+        phrase = []
+        for token_index, token in enumerate(accepted):
+            phrase.append(token)
+            if BOUNDARY.search(token[0]) or token_index == len(accepted) - 1:
+                text = "".join(part[0] for part in phrase)
+                if text.strip():
+                    result.append({"start_ms": offset_ms + phrase[0][1],
+                                   "end_ms": offset_ms + phrase[-1][1], "text": text,
+                                   "original_segment_index": index,
+                                   "original_start_ms": original["start_ms"],
+                                   "original_end_ms": original["end_ms"]})
+                phrase = []
+    if len(result) > 10000:
+        raise ValueError("Oversized DTW passages")
+    return result