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Get Started Free →This skill should be used when the user asks to "convert audio to srt", "generate subtitles from audio", "create srt from mp3/wav/m4a/flac", "transcribe audio to subtitles", or needs to generate SRT subtitle files from audio files (MP3, WAV, M4A, FLAC, etc.) with customizable character limits and timeline adjustments.
.claude/skills/dean9703111-audio-to-srt-converter/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | -33% | 0% |
| case-08 | ✗→✓ | ▲ Improved | -37% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 43% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -58% | 0% |
| case-11 | ✗→✓ | ▲ Improved | -58% | 0% |
This skill provides a Python-based workflow for converting audio files (MP3, WAV, M4A, FLAC, etc.) into SRT subtitle files with automatic speech recognition, customizable text formatting, and timeline optimization.
Convert audio files (MP3, WAV, M4A, FLAC, etc.) into properly formatted SRT subtitle files with:
origin.srtUse this skill when:
Before processing, validate:
Process the audio file using speech recognition:
Format transcribed text according to parameters:
Adjust subtitle timing:
Create final SRT file:
origin.srtThe main conversion script is located at scripts/audio_to_srt.py.
bashpython scripts/audio_to_srt.py <audio_file> [--max-chars MAX_CHARS]
audio_file (required): Path to the input audio file (MP3, WAV, M4A, FLAC, etc.)--max-chars (optional): Maximum characters per subtitle line (default: 22, minimum: 4)See examples/usage_example.sh for complete usage examples.
The script requires the following Python packages:
openai-whisper - For speech recognitionpydub - For audio processingffmpeg - System dependency for audio handlingInstall with:
bashpip install openai-whisper pydub brew install ffmpeg # macOS
The generated SRT file follows this format:
1
00:00:00,000 --> 00:00:03,500
這是第一行字幕
2
00:00:03,500 --> 00:00:07,200
這是第二行字幕scripts/audio_to_srt.py - Main conversion script with environment validationscripts/check_environment.py - Standalone environment checkerexamples/usage_example.sh - Complete usage examples with different parameters| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 15,500 | 16,845 | +9% | 1 | 1 | 0% | 1,775 | 1,219 | -31% | 0 | 0 | — |
case-02 | fail→fail | 9,772 | 15,525 | +59% | 1 | 1 | 0% | 1,695 | 1,064 | -37% | 0 | 0 | — |
case-03 | fail→fail | 13,071 | 6,062 | -54% | 1 | 1 | 0% | 2,494 | 1,247 | -50% | 0 | 0 | — |
case-04 | pass→pass | 15,657 | 8,534 | -45% | 1 | 1 | 0% | 1,541 | 2,077 | +35% | 0 | 0 | — |
case-05 | pass→pass | 18,571 | 14,045 | -24% | 1 | 1 | 0% | 2,062 | 2,639 | +28% | 0 | 0 | — |
case-06 | pass→pass | 19,811 | 14,685 | -26% | 1 | 1 | 0% | 2,492 | 2,744 | +10% | 0 | 0 | — |
case-07 | fail→pass | 10,157 | 3,435 | -66% | 1 | 1 | 0% | 1,854 | 1,250 | -33% | 0 | 0 | — |
case-08 | fail→pass | 10,934 | 1,950 | -82% | 1 | 1 | 0% | 1,831 | 1,158 | -37% | 0 | 0 | — |
case-09 | fail→pass | 5,505 | 1,996 | -64% | 1 | 1 | 0% | 862 | 1,230 | +43% | 0 | 0 | — |
case-10 | fail→pass | 16,720 | 2,481 | -85% | 1 | 1 | 0% | 2,978 | 1,247 | -58% | 0 | 0 | — |
case-11 | fail→pass | 18,613 | 2,796 | -85% | 1 | 1 | 0% | 3,128 | 1,301 | -58% | 0 | 0 | — |
case-12 | fail→pass | 11,775 | 2,086 | -82% | 1 | 1 | 0% | 2,056 | 1,178 | -43% | 0 | 0 | — |
case-13 | fail→pass | 15,325 | 2,156 | -86% | 1 | 1 | 0% | 3,027 | 1,203 | -60% | 0 | 0 | — |
case-14 | fail→pass | 9,475 | 2,250 | -76% | 1 | 1 | 0% | 1,655 | 1,241 | -25% | 0 | 0 | — |
case-15 | pass→pass | 6,383 | 3,954 | -38% | 1 | 1 | 0% | 1,036 | 1,373 | +33% | 0 | 0 | — |
case-16 | fail→pass | 7,841 | 1,769 | -77% | 1 | 1 | 0% | 1,126 | 1,103 | -2% | 0 | 0 | — |
case-17 | pass→pass | 9,601 | 4,383 | -54% | 1 | 1 | 0% | 1,528 | 1,624 | +6% | 0 | 0 | — |
case-18 | pass→pass | 5,262 | 3,073 | -42% | 1 | 1 | 0% | 954 | 1,283 | +34% | 0 | 0 | — |
case-19 | pass→pass | 14,682 | 6,102 | -58% | 1 | 1 | 0% | 2,374 | 1,757 | -26% | 0 | 0 | — |
case-20 | pass→pass | 6,669 | 1,648 | -75% | 1 | 1 | 0% | 858 | 1,007 | +17% | 0 | 0 | — |
case-21 | pass→pass | 2,537 | 2,117 | -17% | 1 | 1 | 0% | 298 | 1,093 | +267% | 0 | 0 | — |
case-22 | pass→pass | 10,013 | 2,776 | -72% | 1 | 1 | 0% | 1,654 | 1,296 | -22% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 19 counted toward the lift figure. The other 3 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +41 percentage points is the difference between those two pass rates over the 19 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.