Transform subtitle line lengths, splitting into multiple subtitle fragments if necessary.
Project description
SRT Equalizer
A Python module to transform subtitle line lengths, splitting into multiple subtitle fragments if necessary. Useful to adjust automatic speech recognition outputs from e.g. Whisper to a more convenient size.
This library works for all languages where spaces separate words.
Installing
pip install srt_equalizer
Example
If the SRT file contains lines over a certain length like this:
1
00:00:00,000 --> 00:00:04,000
Good evening. I appreciate you giving me a few minutes of your time tonight
2
00:00:04,000 --> 00:00:11,000
so I can discuss with you a complex and difficult issue, an issue that is one of the most profound of our time.
Using this code to shorten the subtitles to a maximum length of 42 chars:
from srt_equalizer import srt_equalizer
srt_equalizer.equalize_srt_file("test.srt", "shortened.srt", 42)
...they are split into multiple fragments and time code is adjusted to the approximate proportional length of each segment while staying inside the time slot for the fragment.
1
00:00:00,000 --> 00:00:02,132
Good evening. I appreciate you giving me
2
00:00:02,132 --> 00:00:04,000
a few minutes of your time tonight
3
00:00:04,000 --> 00:00:06,458
so I can discuss with you a complex and
4
00:00:06,458 --> 00:00:08,979
difficult issue, an issue that is one of
5
00:00:08,979 --> 00:00:11,000
the most profound of our time.
Adjust Whisper subtitle lengths
Is is also possible to work with the subtitle items with the following utility methods:
split_subtitle(sub: srt.Subtitle, target_chars: int=42, start_from_index: int=1) -> list[srt.Subtitle]:
whisper_result_to_srt(segments: list[dict]) -> list[srt.Subtitle]:
Here is an example of how to reduce the lingth of subtitles created by Whisper. It assumes you have an audio file to transcribe called gwb.wav.
import whisper
from srt_equalizer import srt_equalizer
import srt
from datetime import timedelta
options_dict = {"task" : "transcribe", "language": "en"}
model = whisper.load_model("small")
result = model.transcribe("gwb.wav", language="en")
segments = result["segments"]
subs = srt_equalizer.whisper_result_to_srt(segments)
# Reduce line lenth in the whisper result to <= 42 chars
equalized = []
for sub in subs:
equalized.extend(srt_equalizer.split_subtitle(sub, 42))
for i in equalized:
print(i.content)
Contributing
This library is built with Poetry. Checkout this repo and run poetry install
in the source folder. To run tests use poetry run pytest tests
.
If you want to explore the library start a poetry shell
.
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