fix(subtitles): tolerate regressing word timestamps

SRT conversion previously rejected otherwise valid word timestamps when a
start preceded the previous word's start. Clamp regressing starts to the
preceding nonempty word's start and extend ends only when necessary.
Preserve transcript order and the original response while continuing to
reject malformed timestamps. Document the adjustment and cover regressions,
cue boundaries, blank words, and invalid input.

Test Plan:
- python3 -B -m unittest -v: all eight tests passed.
- CLI conversion of a synthetic regressing response: passed.
- git diff --cached --check: passed.
- Actual recording verification blocked by unavailable 1Password auth.
This commit is contained in:
2026-09-05 16:27:03 +02:00
parent 4d7fcb1c8f
commit f8e50e4a3e
3 changed files with 55 additions and 5 deletions
+5 -2
View File
@@ -20,8 +20,11 @@ Words are grouped into cues of at most two lines (42 characters per line,
except an unusually long unbroken word) and six seconds. Cues also break at
sentence endings, pauses of at least 0.7 seconds, and speaker changes when
speaker labels are available. Timing comes from the words, rounded to
milliseconds. Subtitle output goes to stdout; missing or invalid word timestamps
produce an error. Without `--srt`, output remains plain text.
milliseconds. If word start times move backwards, they are clamped to the
preceding word's start without reordering the transcript; end times are extended
to the adjusted start only when needed. Subtitle output goes to stdout; missing
or invalid word timestamps produce an error. Without `--srt`, output remains
plain text.
One file per invocation; the whole recording is sent in one request, so
the service's audio length and request size limits apply.
+8 -3
View File
@@ -59,12 +59,17 @@ def convert(response):
or end < start
):
raise ValueError("Invalid subtitle word: expected finite 0 <= start <= end")
if start < previous_start:
raise ValueError("Invalid subtitle words: timestamps are out of order")
previous_start = start
word = dict(item, word=" ".join(item["word"].split()))
if not word["word"]:
continue
# Keep transcript order even when the model's word alignment moves
# backwards. Sorting by time would scramble the spoken text. Clamp
# only regressing starts, retaining the end unless it now precedes
# the start. Work on a copy so the API response remains unchanged.
start = max(start, previous_start)
end = max(end, start)
word.update(start=start, end=end)
previous_start = start
if len(lines(word["word"])) > 2:
raise ValueError("Invalid subtitle word: text exceeds two lines")
if current:
+42
View File
@@ -1,3 +1,4 @@
import copy
import unittest
from subtitles import convert, timestamp
@@ -60,11 +61,52 @@ class SubtitleTests(unittest.TestCase):
{"text": "speech", "words": []},
{"words": [{"word": "bad", "start": 2, "end": 1}]},
{"words": [{"word": "bad", "start": float("nan"), "end": 1}]},
{"words": [{"word": "bad", "start": -1, "end": 1}]},
{"words": [{"word": "bad", "start": 0, "end": float("inf")}]},
{"words": [{"word": "bad", "start": True, "end": 1}]},
{"error": {"message": "failed"}},
):
with self.assertRaises(ValueError):
convert(response)
def test_regressing_timestamps_preserve_text_and_response(self):
response = {"words": [
{"word": "Glasfaser", "start": 10, "end": 10.4},
{"word": "mit", "start": 9.8, "end": 10.2},
{"word": "10", "start": 9.7, "end": 9.9},
{"word": "Gbit/s", "start": 10.5, "end": 11},
]}
original = copy.deepcopy(response)
self.assertEqual(
convert(response),
"1\n00:00:10,000 --> 00:00:11,000\nGlasfaser mit 10 Gbit/s\n\n",
)
self.assertEqual(response, original)
def test_regression_across_cues_and_zero_duration(self):
self.assertEqual(convert({"words": [
{"word": "First", "start": 10, "end": 11, "speaker": 0},
{"word": "Second", "start": 9, "end": 9.5, "speaker": 1},
{"word": "Third", "start": 12, "end": 13, "speaker": 0},
]}), (
"1\n00:00:10,000 --> 00:00:11,000\nFirst\n\n"
"2\n00:00:10,000 --> 00:00:10,001\nSecond\n\n"
"3\n00:00:12,000 --> 00:00:13,000\nThird\n\n"
))
def test_blank_words_do_not_shift_timing(self):
self.assertEqual(convert({"words": [
{"word": " ", "start": 20, "end": 21},
{"word": "Speech", "start": 10, "end": 11},
]}), "1\n00:00:10,000 --> 00:00:11,000\nSpeech\n\n")
def test_regression_does_not_hide_invalid_duration(self):
with self.assertRaises(ValueError):
convert({"words": [
{"word": "valid", "start": 10, "end": 11},
{"word": "invalid", "start": 9, "end": 8},
]})
def test_empty_and_rounding(self):
self.assertEqual(convert({"words": [], "text": ""}), "")
self.assertEqual(timestamp(59.9996), "00:01:00,000")