video-translation
by NoizAIThe video-translation skill translates spoken content in a video into another language, generates TTS dubbing, and replaces or mixes audio while keeping the video intact. It is best for practical video-translation usage when you have a source video, subtitles, and a target language for Translation.
This skill scores 74/100, which means it is list-worthy but best presented with clear caveats. Directory users get a real, non-placeholder workflow for translating and dubbing videos, with explicit triggers and supporting scripts, but they should expect to do some integration work because the repo does not fully spell out an end-to-end install/run path.
- Explicit trigger phrases and use cases make it easy for an agent to recognize when to use the skill.
- The SKILL.md provides a concrete workflow for downloading subtitles, translating them sentence by sentence, and replacing the audio track.
- Supporting scripts for audio replacement and SRT ducking show real operational intent beyond a generic prompt.
- The workflow depends on another skill (`youtube-downloader`) and external tooling like ffmpeg, so installation and execution may require extra setup.
- There is no install command and the excerpted workflow is partially truncated, which reduces immediate out-of-the-box clarity for directory users.
Overview of video-translation skill
What video-translation does
The video-translation skill translates spoken content in a video into another language, generates dubbed audio with TTS, and replaces the original audio while keeping the video itself intact. It is best for users who have a specific video, a target language, and a desire to make the audio watchable rather than just machine-translated on screen.
Who should use it
This video-translation skill fits people localizing YouTube-style content, internal training clips, explainers, or any short-to-medium video where subtitle timing is available or can be extracted. It is less useful if you only need captions, if the source audio is too noisy for subtitle alignment, or if you want human-grade lip sync rather than a practical dubbed version.
What matters before install
The main decision point is workflow fit: video-translation assumes you can obtain the source video plus subtitles, translate subtitle text carefully, produce TTS audio, then mux the result back into the video. If your stack already includes video download, subtitle handling, and ffmpeg-based editing, the skill is a good fit; if not, expect extra setup around those dependencies.
How to Use video-translation skill
Install and inspect the skill
Use video-translation install in the directory toolchain, or install from the repo path with npx skills add NoizAI/skills --skill video-translation. After install, read SKILL.md first, then check scripts/replace_audio.sh and scripts/srt_to_duck.py so you understand how the audio replacement and subtitle-driven ducking actually work.
Turn a rough request into a usable prompt
For best video-translation usage, provide the video URL or file path, source language, target language, and whether you want full dub replacement or mixed audio. A weak prompt is “translate this video”; a stronger one is: “Translate this Spanish YouTube video to English, generate natural-sounding English TTS, and replace the original audio while preserving subtitle timing and silence gaps.”
Practical workflow that matches the repo
The repo’s logic is: download the video and subtitles, translate the SRT sentence by sentence, generate dubbed audio, then replace or mix audio with ffmpeg. If subtitles exist, the helper script can duck the original audio during spoken segments, which usually sounds better than a hard cut. If subtitles are missing or misaligned, expect lower output quality because the timing layer is part of the value.
What to check first in the repo
Start with SKILL.md for trigger intent, workflow order, and the translation prompt shape. Then open scripts/replace_audio.sh to see required flags like --video, --audio, --output, and optional --srt, and inspect scripts/srt_to_duck.py if you need to understand how subtitle timestamps are converted into ducking commands. Those two scripts tell you more about real usage than the high-level description alone.
video-translation skill FAQ
Is video-translation just a prompt template?
No. The video-translation skill is a workflow-oriented setup, not just a wording hint. It depends on subtitle extraction, translation with stable SRT formatting, TTS generation, and audio replacement, so it is more operational than a generic “translate this video” prompt.
When is video-translation a good fit?
Use video-translation when the goal is dubbed playback in another language and the source video can be processed locally or through your existing tools. It is especially useful for educational videos, interviews, and narrated content where preserving the visual track matters more than perfect speech cloning.
What are the main limits?
The biggest limits are subtitle quality, audio quality, and timing alignment. If the source transcript is wrong, the translated dub will inherit those errors; if the TTS voice is unnatural, the result will still sound dubbed; and if the video has overlapping speakers, the ducking-based mix may not be clean.
Do beginners need extra tooling?
Yes, usually. video-translation assumes comfort with files, subtitles, and command-line video tools. If you are new, the skill can still help, but expect to review helper scripts and verify ffmpeg, subtitle, and TTS steps before trusting the first output.
How to Improve video-translation skill
Give better input, not just more input
The strongest video-translation guide starts with clear source and target languages, the exact video file or URL, and the intended audience. Say whether you want formal or colloquial speech, whether names and technical terms should stay untranslated, and whether the final output should preserve pauses for natural timing.
Reduce the common failure modes
Most weak results come from bad subtitles, untranslated proper nouns, or TTS that ignores punctuation and sentence boundaries. To improve video-translation for Translation, verify the SRT before dubbing, keep index and timestamp formatting unchanged, and split long subtitle lines into natural speech units before generating audio.
Iterate after the first render
Treat the first pass as a timing test, not the final deliverable. If the dub sounds rushed, lengthen pauses in the source text or adjust sentence segmentation; if the mix is too aggressive, revisit the SRT-driven ducking behavior; if the wording feels literal, rewrite the subtitle translation prompt to demand colloquial, spoken-language output.
Use the scripts to sharpen quality
The repo’s helper scripts are a clue to what matters: timing, replacement, and stable audio switching. If you are improving the video-translation skill for repeated use, build a small checklist around subtitle accuracy, TTS voice choice, and final mux verification so the same errors do not recur on every video.