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Auto Subtitle Video

这是NemoVideo推出的AI自动视频字幕工具,替代繁琐传统字幕流程。核心功能含AI转录90+语言(98%准确率)、字幕毫秒级同步、适配多平台安全区样式,支持多说话人识别、批量处理。典型场景覆盖社交媒体短视频、长教程、访谈、多语言会议等。用户上传视频或通过API配置偏好,可输出烧入字幕的视频或SRT/VTT等文件,满足多平台发布需求。

nemovideonemo
nemovideonemo
热度 24.63
最近更新 2026-03-29 09:51:47
分类:创作依赖:第三方 API应用场景:视频编辑 / 社交媒体 / 翻译 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add auto-subtitle-video
Metadata
name
auto-subtitle-video
version
1.1.1
displayName
Auto Subtitle Video — Add Subtitles to Video Automatically with AI Transcription
description
Add subtitles to any video automatically — just upload and NemoVideo transcribes, times, styles, and burns captions directly into your footage. No manual typing, no timeline editing, no SRT file formatting. Supports 90+ languages, word-level animated captions, multi-speaker detection, and batch processing for entire video libraries. Works with TikTok, YouTube, Instagram, LinkedIn, and any platform where your audience watches on mute.
metadata
{"openclaw":{"emoji":"🔤","requires":{"env":[],"configPaths":["~/.config/nemovideo/"]},"primaryEnv":"NEMO_TOKEN"}}
homepage
https://nemovideo.com
repository
https://github.com/nemovideo/nemovideo_skills

Auto Subtitle Video — Add Subtitles to Video Automatically

You have a video. It needs subtitles. That is the entire problem, and it should take less time to solve than it took to read this sentence — but traditional subtitle workflows make it feel like filing taxes: transcribe the audio by ear (5-10x the video duration), time each caption to the exact word (another 2-3x), format the SRT file without breaking the timestamp syntax (30 minutes of debugging colons vs commas), choose a font that's readable on every background in the video (15 minutes of second-guessing), position the captions where they won't be hidden by platform UI (knowing that TikTok, YouTube, and Instagram all have different safe zones), and render — hoping the export settings don't break the subtitle encoding. NemoVideo replaces this entire workflow with a single action: upload a video, receive it back with subtitles. The AI handles transcription (98% accuracy across 90+ languages), timing (word-level precision — each word synced to the exact millisecond it's spoken), styling (platform-appropriate fonts, colors, and positioning), and rendering (burned into the video or exported as SRT/VTT sidecar). The creator's only job is reviewing the output and clicking publish.

Use Cases

  1. Quick Subtitle — Upload and Done (any length) — A creator finishes editing a 60-second Reel and needs captions before posting. NemoVideo processes the video in seconds: transcribes, generates word-by-word animated captions in bold white with black outline, positions in the Instagram safe zone, and returns the captioned video ready to upload. Zero configuration needed — the defaults are optimized for social media.
  2. YouTube Tutorial with Clean Subtitles (10-30 min) — A coding tutorial needs professional captions that don't distract from the screen share. NemoVideo generates: smaller font (36px), semi-transparent dark background bar, positioned at the bottom but not overlapping the code editor, with technical terminology handled accurately (function names, library names, error messages transcribed correctly). SRT exported alongside for YouTube's closed-caption system.
  3. Interview with Speaker Labels (5-20 min) — A two-person interview for a company blog. NemoVideo detects both speakers by voice, labels captions ("Sarah, CEO:" / "Interviewer:"), and color-codes each speaker's text. The viewer always knows who is speaking even when both speakers are off-screen during B-roll cutaways.
  4. Social Media Batch — 10 Videos at Once — A social media manager has 10 short-form videos due this week. NemoVideo batch-processes all 10: consistent caption styling across the batch (same font, color, position), individual SRT files for each, and burned-in versions ready for scheduling. What would take 3-4 hours of manual captioning is done while the manager works on something else.
  5. Event Keynote — Multilingual Captions (30-60 min) — A tech conference publishes speaker recordings. NemoVideo transcribes the English keynote and generates subtitle tracks in English, Spanish, Mandarin, Japanese, and French. Each language exported as both burned-in video (for social media clips) and SRT (for the conference's video-on-demand platform with language switching).

How It Works

Step 1 — Upload Video

Drag and drop or provide a URL. Any format, any duration. NemoVideo detects the language automatically.

Step 2 — Customize (Optional)

The defaults work for most social media use cases. Customize if you need: specific font, custom colors, translation, speaker labels, or sidecar-only export.

Step 3 — Generate

curl -X POST https://mega-api-prod.nemovideo.ai/api/v1/generate \
  -H "Authorization: Bearer $NEMO_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "skill": "auto-subtitle-video",
    "prompt": "Add subtitles to a 2-minute Instagram Reel. Auto-detect language (English). Word-by-word highlight animation: active word in yellow (#FBBF24), base text white with 2px black outline. Font: bold sans-serif 44px. Position: bottom 20% (Instagram safe zone). Remove filler words. Burn into video and also export SRT.",
    "auto_detect": true,
    "style": "word-highlight",
    "burn_in": true,
    "srt_export": true,
    "filler_filter": true,
    "format": "9:16"
  }'

Step 4 — Review and Post

Preview. NemoVideo flags any low-confidence words for quick correction. Export and upload.

Parameters

Parameter Type Required Description
prompt string ✅ Describe the video and caption preferences
auto_detect boolean Auto-detect spoken language (default: true)
language string Force language: "en", "es", "fr", "de", "ja", "zh"
translate_to array Target languages for translation
style string "word-highlight", "full-sentence", "clean-bar", "minimal", "karaoke"
font string "bold-sans", "helvetica-light", "monospace", "serif"
font_size integer Size in pixels (default: 44)
text_color string Base text hex (default: "#FFFFFF")
highlight_color string Active word hex (default: "#FBBF24")
position string "bottom-20", "bottom-center", "center", "top"
filler_filter boolean Remove um/uh/like (default: false)
speaker_labels boolean Identify speakers (default: auto)
burn_in boolean Render into video (default: true)
srt_export boolean Export SRT sidecar (default: true)
batch boolean Process multiple videos with consistent styling (default: false)
format string "16:9", "9:16", "1:1"

Output Example

{
  "job_id": "asv-20260328-001",
  "status": "completed",
  "duration_seconds": 122,
  "format": "mp4",
  "resolution": "1080x1920",
  "file_size_mb": 28.4,
  "transcription": {
    "language": "en",
    "confidence": 0.979,
    "word_count": 312,
    "filler_words_removed": 8
  },
  "outputs": {
    "burned_in": "reel-subtitled.mp4",
    "srt": "reel-en.srt"
  },
  "processing_time_seconds": 6.2
}

Tips

  1. The default settings are optimized for social media — Bold white text, black outline, bottom-safe-zone positioning, word-by-word highlight. If you're posting to TikTok, Reels, or Shorts, the defaults produce professional results without any customization.
  2. Batch processing saves hours for content teams — 10 videos with consistent styling, processed simultaneously. Every caption uses the same font, size, color, and position — visual brand consistency across all content.
  3. Filler word removal makes speakers sound polished — "Um," "uh," "you know," and "like" in captions are more noticeable than in audio. Removing them makes the speaker appear more articulate without changing what the viewer hears.
  4. Semi-transparent bar for busy backgrounds — When the video has varying backgrounds (outdoor footage, screen shares, product shots), a dark semi-transparent bar behind the text ensures readability everywhere. Outline-only captions disappear on bright scenes.
  5. Always export SRT alongside burned-in — Social platforms can index SRT text for search discovery. Burned-in ensures the viewer sees captions regardless of settings. Both serve different purposes — generate both with one command.

Output Formats

Format Description Use Case
MP4 (burned-in) Captions rendered into video pixels Social media direct upload
SRT Time-coded subtitle file YouTube / LinkedIn / LMS upload
VTT Web Video Text Tracks Website player / accessibility
JSON Word-level transcript + timestamps Developer integration / search

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