Translate Video

End-to-end video translation pipeline. Takes a video, transcribes it, translates to target language with native-speaker refinement, and burns subtitles onto the video.

Usage

/translate-video /path/to/video.mp4 he
/translate-video /path/to/video.mp4 ar
/translate-video /path/to/video.mp4 es

Arguments:

• $1 - Path to video file (required)
• $2 - Target language code (default: he). Codes: he, ar, es, fr, de, ru, zh, ja, etc.

Pipeline

Step 1: Transcribe (via /transcribe skill)

Extract audio if video is too large (>25MB audio), then transcribe:

# Extract audio if needed (reduces upload size)
ffmpeg -i "$VIDEO" -vn -acodec libmp3lame -ab 128k "$AUDIO_PATH" -y

# Transcribe using the transcribe skill's script
cd ~/.claude/skills/transcribe/scripts && [ -d node_modules ] || npm install --silent
npx ts-node transcribe.ts -i "$INPUT" -o "$SRT_PATH"

This generates:

• {basename}.srt - Raw SRT file
• {basename}.md - Readable text

Step 2: Translate

Read the .md file to understand full context, then translate the .srt file.

Translation rules:

• Translate ALL subtitle text entries, preserving SRT index numbers and timestamps exactly
• Do NOT translate proper nouns (product names, people's names, brand names)
• Keep technical terms that are commonly used untranslated in the target language (API, CLI, SaaS, etc.)
• Adapt idioms and expressions to natural equivalents in the target language
• Match the speaker's register (casual/formal) in the translation

Step 3: Semantic Refinement

The raw transcription chunks by time, not meaning. Regroup for the target language:

1. Read all translated text as continuous prose
2. Identify natural sentence/clause boundaries in the target language
3. Regroup words into semantically coherent subtitle entries (max 2 lines per entry, ~40 chars per line)
4. Adjust timestamps: each entry starts at first word's original time, ends at last word's time
5. Merge fragmented entries - aim for 150-250 entries for a ~15min video (vs 500-600 raw)
6. Native speaker test - read each subtitle aloud. If it sounds awkward, rephrase

Quality checklist:

• No sentence split mid-clause
• No orphaned words (single word carrying over from previous thought)
• Punctuation at natural break points
• Reading pace is comfortable (not too much text per subtitle)
• Sounds like a native speaker wrote it, not a translation

Step 4: Embed Subtitles (via /embed-subtitles skill)

RTL is handled automatically by the embed-subtitles skill - it detects RTL content and applies Unicode directional marks before embedding. No need to handle RTL here.

Burn the translated SRT onto the video:

cd ~/.claude/skills/embed-subtitles/scripts
npx ts-node embed-subtitles.ts \
  -i "$VIDEO" \
  -s "$TRANSLATED_SRT" \
  -o "$OUTPUT" \
  --font-size 24 --margin 30

Or directly with FFmpeg:

ffmpeg -i "$VIDEO" \
  -vf "subtitles='$TRANSLATED_SRT':force_style='FontName=Arial,FontSize=24,PrimaryColour=&H00FFFFFF,OutlineColour=&H00000000,Outline=2,Shadow=1,Alignment=2,MarginV=30'" \
  -c:v libx264 -preset fast -crf 23 -c:a copy \
  "$OUTPUT" -y

Step 5: Open Result

open "$OUTPUT"  # macOS

Output Files

All files saved next to the original video:

Language Codes

Examples

Hebrew translation (most common use):

/translate-video ~/Desktop/tutorial.mp4 he

Produces: tutorial_he.srt + tutorial_he_subtitled.mp4

Spanish translation:

/translate-video ~/Desktop/talk.mp4 es

Default (Hebrew):

/translate-video ~/Desktop/video.mp4