# Audio Glitch Detector
[](https://badge.fury.io/py/audio-glitch-detector)
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
Detect audio glitches and discontinuities in sinusoidal audio signals by analyzing the signal derivative.
**Important:** This tool is will only work with sinusoidal audio signals.
### Limitations
The algorithm detects discontinuities, so glitches that does not directly produce discontinuities might not be picked up.
It can detect single sample errors in a sine wave. The test files in `test_files/` show cases where the algorithm works well.
## Installation
### From PyPI
```bash
pip install audio-glitch-detector
```
### From source with uv (development)
```bash
git clone https://github.com/kaspernyhus/audio-glitch-detector
cd audio-glitch-detector
uv sync --dev
```
## Quick Start
### Command Line Usage
Analyze a WAV file with automatic threshold:
```bash
audio-glitch-detector -f path/to/audio.wav
```
Monitor live audio stream:
```bash
audio-glitch-detector
```
Save glitch blocks for analysis:
```bash
audio-glitch-detector -f audio.wav --save-blocks
```
### Library Usage
see `examples/` for usage examples.
## Visual Analysis
When using `--save-blocks`, glitch blocks (max 50) are saved as .wav files and with waveform visualizations showing the derivative analysis:
## Test Files
Validate the detector with test files with a known number of discontinuities:
```bash
audio-glitch-detector -f test_files/sine_discont_2_mono.wav
```
Expected output:
```
Number of discontinuities detected: 2
0:00:01.892857
0:00:03.288367
```
## How It Works
1. **Derivative Analysis**: Calculates the first derivative of audio samples
2. **Threshold Detection**: Uses 99.5th percentile of derivative distribution
3. **Peak Identification**: Finds samples exceeding the threshold
## Development
### Setup
```bash
uv sync --dev
```
### Run the application
```bash
uv run audio-glitch-detector --help
```
### Run tests
```bash
uv run pytest
```
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"description": "# Audio Glitch Detector\n\n[](https://badge.fury.io/py/audio-glitch-detector)\n[](https://www.python.org/downloads/)\n[](https://opensource.org/licenses/MIT)\n\nDetect audio glitches and discontinuities in sinusoidal audio signals by analyzing the signal derivative.\n\n**Important:** This tool is will only work with sinusoidal audio signals.\n\n### Limitations\nThe algorithm detects discontinuities, so glitches that does not directly produce discontinuities might not be picked up.\nIt can detect single sample errors in a sine wave. The test files in `test_files/` show cases where the algorithm works well.\n\n## Installation\n\n### From PyPI\n```bash\npip install audio-glitch-detector\n```\n\n### From source with uv (development)\n```bash\ngit clone https://github.com/kaspernyhus/audio-glitch-detector\ncd audio-glitch-detector\nuv sync --dev\n```\n\n## Quick Start\n\n### Command Line Usage\n\nAnalyze a WAV file with automatic threshold:\n```bash\naudio-glitch-detector -f path/to/audio.wav\n```\n\nMonitor live audio stream:\n```bash\naudio-glitch-detector\n```\n\nSave glitch blocks for analysis:\n```bash\naudio-glitch-detector -f audio.wav --save-blocks\n```\n\n### Library Usage\n\nsee `examples/` for usage examples.\n\n\n## Visual Analysis\n\nWhen using `--save-blocks`, glitch blocks (max 50) are saved as .wav files and with waveform visualizations showing the derivative analysis:\n\n\n\n## Test Files\n\nValidate the detector with test files with a known number of discontinuities:\n```bash\naudio-glitch-detector -f test_files/sine_discont_2_mono.wav\n```\n\nExpected output:\n```\nNumber of discontinuities detected: 2\n0:00:01.892857\n0:00:03.288367\n```\n\n\n## How It Works\n\n1. **Derivative Analysis**: Calculates the first derivative of audio samples\n2. **Threshold Detection**: Uses 99.5th percentile of derivative distribution\n3. **Peak Identification**: Finds samples exceeding the threshold\n\n\n## Development\n\n### Setup\n```bash\nuv sync --dev\n```\n\n### Run the application\n```bash\nuv run audio-glitch-detector --help\n```\n\n### Run tests\n```bash\nuv run pytest\n```\n",
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