pyavsubs

Here you can find the software I use to manage the process/team involved in Italian subtitles creation for (long) YouTube videos, in case it could be useful for someone else. This is a Python port of this R package: the dependencies are srt and matplotlib libraries.

Our first subbed video was this one; we're now completing Gary's mix.

Here is the background machinery, the repository with the subs themselves is here.

Usage

If you want to make your own subs have some programming skill and want to reuse our software, install this package, open a python3 interpreter in the subs directory (for me it's the clone of this repo on my machine), then

from pyavsubs.Prj import Prj
Prj(id = 'gymix', yt_id = 'Lox6tAor5Xo').menu()

where gymix is the project id (which maps to the directory under subs), while lw53nODhRXU is the YouTube id of the support video used for translations. After commanding menu, an interactive menu is given:

=========================
        MAIN MENU        
=========================

Select a number or 0 to exit 

1. Setup
2. Create sandboxes
3. Assign TRN or REV2
4. Mark progresses
5. Monitoring
6. List available REV1
7. List available REV2
8. Make final srt
9. Final SRT stats
10. List assignee
11. List users 

Selection (0 to exit): 

where:

1. Setup: create the project directory under subs and split a source sub (derived from YT automatic sub generator) into 5min length chunks

2. Create sandboxes: set up test files for translator and revisors

3. Assign TRN or REV2: assign a chunk to be translated or revised (readability revision)

4. Mark progresses: update progress information for monitoring purposes (eg which translation are completed, which revision are started, completed and so on)

5. Monitoring: make a monitorin graph

6. List available REV1: list files translated but not linguistically revised yet

7. List available REV2: list files linguistically revised but not from a readability standpoint yet

8. Make final srt: compose the final .srt by collapsing revised files

9. Final SRT stats: compute the readability stats for the final .srt in order to spot subs which are difficult to read

10. List assignee: list all chunks and assigned translator/revisors for each of them

11. List users: list all the users in the data/users.csv "database"