# pyAudioAnalysis

**Repository Path**: tang_bowen/pyAudioAnalysis

## Basic Information

- **Project Name**: pyAudioAnalysis
- **Description**: Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-14
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README


# <img src="icon.png" align="left" height="130"/> A Python library for audio feature extraction, classification, segmentation and applications

*This doc contains general info. Click [here](https://github.com/tyiannak/pyAudioAnalysis/wiki) for the complete wiki*

## News
 * If you like this library and [my articles](https://hackernoon.com/u/tyiannak), please support me at the hackernoon [ML Writer of the Year](https://noonies.tech/award/ml-writer-of-the-year) 
 * Special issue in [Pattern Recognition in Multimedia Signal Analysis](https://www.mdpi.com/journal/applsci/special_issues/Multimedia_Signal), Deadline 30 November 2020
 * [2020-07-20] Related article: [How to Use Machine Learning to Color Your Lighting Based on Music Mood](https://hackernoon.com/how-to-use-machine-learning-to-color-your-lighting-based-on-music-mood-bi163u8l). 
 * [2020-06-05] Read this article titled "Basic Audio Handling" for an intro to audio data handing, on [medium](https://medium.com/behavioral-signals-ai/basic-audio-handling-d4cc9c70d64d) or [hackernoon](https://hackernoon.com/audio-handling-basics-how-to-process-audio-files-using-python-cli-jo283u3y).
 * [2019-11-19] Major lib refactoring. Please report possible issues that have not been fixed, or inconsistencies in the documentation.  
 * Check out [paura](https://github.com/tyiannak/paura) a python script for realtime recording and analysis of audio data
 * [2018-08-12] pyAudioAnalysis now ported to Python 3

## General
pyAudioAnalysis is a Python library covering a wide range of audio analysis tasks. Through pyAudioAnalysis you can:
 * Extract audio *features* and representations (e.g. mfccs, spectrogram, chromagram)
 * *Classify* unknown sounds
 * *Train*, parameter tune and *evaluate* classifiers of audio segments
 * *Detect* audio events and exclude silence periods from long recordings
 * Perform *supervised segmentation* (joint segmentation - classification)
 * Perform *unsupervised segmentation* (e.g. speaker diarization)
 * Extract audio *thumbnails*
 * Train and use *audio regression* models (example application: emotion recognition)
 * Apply dimensionality reduction to *visualize* audio data and content similarities

## Installation
 * Clone the source of this library: `git clone https://github.com/tyiannak/pyAudioAnalysis.git`
 * Install dependencies: `pip install -r ./requirements.txt `
 * Install using pip: `pip install -e .`

## An audio classification example
> More examples and detailed tutorials can be found [at the wiki](https://github.com/tyiannak/pyAudioAnalysis/wiki)

pyAudioAnalysis provides easy-to-call wrappers to execute audio analysis tasks. Eg, this code first trains an audio segment classifier, given a set of WAV files stored in folders (each folder representing a different class) and then the trained classifier is used to classify an unknown audio WAV file

```
from pyAudioAnalysis import audioTrainTest as aT
aT.extract_features_and_train(["classifierData/music","classifierData/speech"], 1.0, 1.0, aT.shortTermWindow, aT.shortTermStep, "svm", "svmSMtemp", False)
aT.file_classification("data/doremi.wav", "svmSMtemp","svm")
Result:
(0.0, array([ 0.90156761,  0.09843239]), ['music', 'speech'])
```

In addition, command-line support is provided for all functionalities. E.g. the following command extracts the spectrogram of an audio signal stored in a WAV file: `python audioAnalysis.py fileSpectrogram -i data/doremi.wav`

## Further reading
Apart from the current README and [the wiki](https://github.com/tyiannak/pyAudioAnalysis/wiki), a more general and theoretic description of the adopted methods (along with several experiments on particular use-cases) is presented [in this publication](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0144610). *Please use the following citation when citing pyAudioAnalysis in your research work*:
```
@article{giannakopoulos2015pyaudioanalysis,
  title={pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis},
  author={Giannakopoulos, Theodoros},
  journal={PloS one},
  volume={10},
  number={12},
  year={2015},
  publisher={Public Library of Science}
}
```

For Matlab-related audio analysis material check  [this book](http://www.amazon.com/Introduction-Audio-Analysis-MATLAB%C2%AE-Approach/dp/0080993885).

## Author
<img src="https://tyiannak.github.io/files/3.JPG" align="left" height="100"/>

[Theodoros Giannakopoulos](https://tyiannak.github.io),
Director of Machine Learning at [Behavioral Signals](https://behavioralsignals.com)