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https://github.com/peterk/srt_equalizer
A Python module to transform subtitle line lengths, splitting into multiple subtitle fragments if necessary.
https://github.com/peterk/srt_equalizer
closed-captions srt subtitles whisper
Last synced: about 13 hours ago
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A Python module to transform subtitle line lengths, splitting into multiple subtitle fragments if necessary.
- Host: GitHub
- URL: https://github.com/peterk/srt_equalizer
- Owner: peterk
- License: mit
- Created: 2023-03-14T11:59:30.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-12-02T06:13:07.000Z (about 1 month ago)
- Last Synced: 2025-01-02T09:19:26.899Z (11 days ago)
- Topics: closed-captions, srt, subtitles, whisper
- Language: Python
- Homepage:
- Size: 50.8 KB
- Stars: 30
- Watchers: 1
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
- Security: SECURITY.md
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README
[](https://securityscorecards.dev/viewer/?uri=github.com/peterk/srt_equalizer) 
# 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](https://github.com/openai/whisper) to a more convenient size.
This library works for all languages where spaces separate words.
## Installing
`pip install srt_equalizer`
## Example
An SRT file containing lines over a certain length can be adjusted to a maximum line length for better readability on screen.
```
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.
```
To adjust line length to a maximum length of 42 chars you can use SRT equalizer like this:
```python
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.
```
### Algorithms
By default, this script uses `greedy` algorithm which splits the text at the rightmost possible space.
An alternative splitting algorithm is `halving` which will split longer lines more evenly instead of always trying to use maximum line length. This prevents producing lines with isolated word remainders.
Another alternative is the `punctuation` algorithm that takes punctuation (commas, periods, etc.) into account.
```python
from srt_equalizer import srt_equalizer
# use "greedy", "halving" or "punctuation" for the method parameter
srt_equalizer.equalize_srt_file("test.srt", "shortened.srt", 42, method='halving')
```
## Adjust Whisper subtitle lengths
Is is also possible to work with subtitle items produced from [Whisper](https://github.com/openai/whisper) with the following utility methods:
```python
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.
```python
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](https://python-poetry.org). Checkout this repo and run `poetry install` in the source folder. To run tests use `poetry run pytest tests`.
To build a new release, create a new tag, build it and publish to pypi:
```
poetry run pytest tests
git tag v0.1.2
poetry build
poetry publish
```
If you want to explore the library start a `poetry shell`.