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Audio to srt

Skill dean9703111/ai-agent-skill-for-video-workflow/.agent/skills/audio-to-srt

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.From its SKILL.md

Install
npx -y skills add dean9703111/ai-agent-skill-for-video-workflow --skill audio-to-srt

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SKILL.md

3.7 KB, 793 tokens by cl100k_base, as published. Nobody here has run it

Audio to SRT Converter

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.

Purpose

Convert audio files (MP3, WAV, M4A, FLAC, etc.) into properly formatted SRT subtitle files with:

  • Automatic speech recognition and transcription
  • Support for multiple audio formats (MP3, WAV, M4A, FLAC, and more)
  • Customizable character limits per subtitle line (default: 22 characters, minimum: 4 characters)
  • Automatic timeline gap filling (gaps < 0.3s are merged)
  • Environment and dependency validation
  • Output naming convention: origin.srt

When to Use This Skill

Use this skill when:

  • Converting audio files to subtitle format
  • Generating transcriptions with timeline information
  • Creating SRT files for video editing or accessibility
  • Processing Chinese or multilingual audio content

Core Workflow

1. Environment Validation

Before processing, validate:

  • Python 3.7+ is installed
  • Required packages are available (see Dependencies section)
  • Input MP3 file exists and is readable
  • Output directory is writable

2. Audio Transcription

Process the audio file using speech recognition:

  • Load audio file (supports MP3, WAV, M4A, FLAC, etc.)
  • Perform speech-to-text conversion
  • Extract timestamps for each segment
  • Handle silence detection and word boundaries

3. Text Formatting

Format transcribed text according to parameters:

  • Split text into lines based on character limit
  • Ensure minimum 4 characters per line
  • Respect word boundaries when possible
  • Handle Chinese character counting correctly

4. Timeline Optimization

Adjust subtitle timing:

  • Identify gaps between subtitle segments
  • Merge segments when gap < 0.3 seconds
  • Extend previous subtitle end time to next subtitle start time
  • Maintain synchronization with audio

5. SRT Generation

Create final SRT file:

  • Format according to SRT specification
  • Number subtitles sequentially
  • Use proper timestamp format (HH:MM:SS,mmm)
  • Save as origin.srt

Using the Conversion Script

The main conversion script is located at scripts/audio_to_srt.py.

Basic Usage

python scripts/audio_to_srt.py <audio_file> [--max-chars MAX_CHARS]

Parameters

  • 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)

Examples

See examples/usage_example.sh for complete usage examples.

Dependencies

The script requires the following Python packages:

  • openai-whisper - For speech recognition
  • pydub - For audio processing
  • ffmpeg - System dependency for audio handling

Install with:

pip install openai-whisper pydub
brew install ffmpeg  # macOS

Output Format

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

Additional Resources

Scripts

  • scripts/audio_to_srt.py - Main conversion script with environment validation
  • scripts/check_environment.py - Standalone environment checker

Examples

  • examples/usage_example.sh - Complete usage examples with different parameters

What ships with it: 1 file

7.0 KB alongside SKILL.md, 1 of them executable

scripts/

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