Automatic Subtitling with Python

Growing up, Comeback was1 one of my favorite Czech sitcoms. Re-watching it recently, I wanted to show it to my friend who doesn’t speak Czech, but English subtitles don’t seem to exist (and, for that matter, neither do Czech ones).

Seeing as I don’t have much time (master thesis), I decided to waste it by creating them. Further seeing as I am a programmer, I am not going to do this manually and, as the title suggests, will automate the process as much as I can.

This short post covers what I did and could prove useful if case you have your own favorite movie/show that you’d like to create subtitles for.

Here are the subtitles, if you’re interested. ←

The general approach for creating subtitles is the following:

  1. use OpenAI’s Whisper to automatically create the initial subtitles & timings
  2. manually fix timing & errors using Kdenlive
  3. use a local LLM (Mistral 7B via ollama) for Czech → English translation
  4. fix errors using a text editor of your choice (e.g. vimdiff)

1) Transcription

To create the initial Czech subtitles (or pretty much any other language2), we’ll first need to install WhisperX, which is a faster and less memory-hungry implementation of Whisper. Assuming you have the preliminaries (CUDA-enabled GPU & PyTorch), you can install WhisperX from source via pip:

pip install git+

To automatically create the subtitles, we can use ffmpeg to extract the audio, and subsequently run the whisperx command with appropriate parameters. Assuming you are in the directory with your audio files, you can run the following script:

for file in *.mp4; do
  # Extract audio (if it doesn't exist)

  if [ ! -s "$audio_file" ]; then
    ffmpeg -y -i "$file" -vn "$audio_file"

  # Create directory for the subtitles
  mkdir -p "$out_dir"

  # Run whisperx + symlink the video (if the directory is empty)
  if [ -z "$(ls -A "$out_dir")" ]; then
    whisperx "$audio_file" \
        --model large-v3 \
        --language Czech \
        --segment_resolution chunk \
        --task transcribe \
        --output_dir "$out_dir" \
        --output_format srt

    ln -s "../../$(basename "$file")" "$out_dir/$(basename "$file")"

Note that for the large WhisperX models, you need to have at least ~8 GB of VRAM. If you don’t have this, use medium, which requires ~6 GB and is quite a bit worse.

If you don’t have a GPU at all, I would recommend using Runpod, which offers cheap GPU devices with custom Docker images. This is not a sponsored post but I am a very happy customer, and if you’d like to support me, here is my referral link.

If you only need to transcribe a short video, you can also use Google Colab for free, since it offers a few hours of GPU access for free.

2) Manual Transcription Fixes

Since the transcription contains some errors in both contents and timing (although I have to say that the results are around 95% correct, which is insanely impressive), we need to fix those. My tool of choice is Kdenlive, since it’s the video editor I’m pretty comfortable with and has good tools for editing subtitles.

I don’t really have much to write here – to edit the subtitles, just drag & drop the video + subtitles and hit play, fixing mistakes along the way. Note that doing this for a 30-minute episode usually takes me around 1 hour, so if it takes you 10 you’re doing something wrong and if it takes you 5 minutes please tell me how.

One helpful thing that I discovered after translating the first ~3 episodes is that Whisper can sometimes produce consistent incorrect results, which you can fix automatically for all future episodes – in my case, the names of the lead characters (mainly Ivuška and Ozzák) made rise to the following replacement rules:

ozák -> Ozzák
Ozák -> Ozzák
ivošk -> Ivušk
Ivošk -> Ivušk

Yet again, here is a Python script that automatically does this for subtitle files in all subdirectories of wherever you’re launching it from:

from pathlib import Path
from tempfile import NamedTemporaryFile
from subprocess import Popen

import re
import shutil

Add -> all
rules -> here.

replacement_rules_list = []
for line in REPLACEMENT_RULES.strip().splitlines():
    source, target = line.strip().split(' -> ')
    replacement_rules_list.append((source, target))

def perform_replacements_in_file(in_path, out_path):
    with open(in_path, 'r') as file:
        content =

    for pattern, replacement in replacement_rules_list:
        content = re.sub(pattern, replacement, content)

    with open(out_path, 'w') as file:

# First do replacements to a temporary file
temp_file_mapping = {}
for file in sorted(Path(".").rglob('*.srt')):
    if not file.is_file():

    with NamedTemporaryFile(delete=False, suffix=".srt") as f:
        out_file = Path(

        temp_file_mapping[file] = out_file
        perform_replacements_in_file(file, out_file)

# Check diffs
for orig, tmp in sorted(temp_file_mapping.items()):
    process = Popen(["diff", "-u", str(orig), str(tmp)])

i = None
while not i or i.lower() not in "yn":
    i = input("Confirm replacement [Y/n]: ")

if i.lower() == "y":
    for orig, tmp in temp_file_mapping.items():
        shutil.move(tmp, orig)
    print("Removing tempfiles...")
    for _, tmp in temp_file_mapping.items():

3) Translation

For a reasonably fast and accurate Czech to English translation, one way is to use a local LLM model for line-by-line translation. I’ve experimented with Whisper’s translation functionality, but it creates problems with timing (since I wanted it to be the same as the Czech subtitles), as well as not being too good.

I will be using ollama with the Mistral 7B, which again requires around ~8 GB of VRAM. If you don’t have this, I would again recommend using Runpod.

To install, run the following (ideally read what the script does first before you pipe it to sh):

curl -fsSL | sh

To perform the translation, we will again run a script in the directory with the videos:

from pathlib import Path
from subprocess import Popen, PIPE
from tempfile import NamedTemporaryFile
from tqdm import tqdm

import shutil

PROMPT = "Translate the following line from a Czech subtitle to English. Only include the response: "

for file in sorted(Path(".").rglob('*.srt')):
    if not file.is_file():

    # Czech -> English
    if != "cz":

    en_file = file.parent.parent / "en" /
    en_file.parent.mkdir(parents=True, exist_ok=True)

    # Skip if it already exists
    if en_file.exists():

    print(f"Translating '{}'...")
    with open(file, "r") as f, NamedTemporaryFile(mode="w", delete=False) as g:
        lines =

        # I hope this is a safe assumption :)
        for i, line in tqdm(enumerate(lines), total=len(lines)):
            if i % 4 != 2:
                g.write(line + "\n")

            process = Popen(["ollama", "run", "mistral", PROMPT + "[" + line.strip() + "]"], stdout=PIPE, stderr=PIPE)

            if i > 10:

            stdout, _ = process.communicate()

            # the LLM sometimes doesn't exactly follow the prompt, so we only keep the first line
            stdout = stdout.decode().strip().splitlines()[0]

            g.write(stdout + "\n")

    shutil.move(, en_file)

4) Manual Translation Fixes

Open the subtitles in your favorite text editor (vim) and fix away.

5) Credits

I also added a link to the page with all Comeback subtitles at the beginning of each individual subtitles, in case people obtain them from somewhere else and would like to get them for other episodes:

from pathlib import Path

EXPORT_DIRECTORY = Path("../Comeback Subtitles")

BEGINNING = "1\n00:00:00,000 --> 00:00:05,000\n\n"

for file in sorted(Path(".").rglob('*.srt')):
    if not file.is_file():

    lang =

    output_directory = EXPORT_DIRECTORY / lang
    output_directory.mkdir(parents=True, exist_ok=True)
    output_file = output_directory /

    with open(file, "r") as f, open(output_file, "w") as g:
        g.write(BEGINNING + "\n")

        for i, line in enumerate(f):
            if i % 4 == 0:
                g.write(f"{i // 4 + 2}\n")
  1. Watching the show back, I have to admit that certain episodes are a little rough to watch and could be considered problematic in today’s day and age. Watch at your own peril. 

  2. Well... almost all:

    Afrikaans, Albanian, Amharic, Arabic, Armenian, Assamese, Azerbaijani, Bashkir, Basque, Belarusian, Bengali, Bosnian, Breton, Bulgarian, Burmese, Cantonese, Castilian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Faroese, Finnish, Flemish, French, Galician, Georgian, German, Greek, Gujarati, Haitian, Haitian Creole, Hausa, Hawaiian, Hebrew, Hindi, Hungarian, Icelandic, Indonesian, Italian, Japanese, Javanese, Kannada, Kazakh, Khmer, Korean, Lao, Latin, Latvian, Letzeburgesch, Lingala, Lithuanian, Luxembourgish, Macedonian, Malagasy, Malay, Malayalam, Maltese, Maori, Marathi, Moldavian, Moldovan, Mongolian, Myanmar, Nepali, Norwegian, Nynorsk, Occitan, Panjabi, Pashto, Persian, Polish, Portuguese, Punjabi, Pushto, Romanian, Russian, Sanskrit, Serbian, Shona, Sindhi, Sinhala, Sinhalese, Slovak, Slovenian, Somali, Spanish, Sundanese, Swahili, Swedish, Tagalog, Tajik, Tamil, Tatar, Telugu, Thai, Tibetan, Turkish, Turkmen, Ukrainian, Urdu, Uzbek, Valencian, Vietnamese, Welsh, Yiddish, Yoruba.