# spafe

**Repository Path**: xinci/spafe

## Basic Information

- **Project Name**: spafe
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: BSD-3-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-04-29
- **Last Updated**: 2024-04-29

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<p align="center">
<img src="logo.png">
</p>

spafe: Simplified Python Audio-Features Extraction
==================================================

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spafe aims to simplify features extractions from mono audio files. The library can extract of the following features: ***BFCC, LFCC, LPC, LPCC, MFCC, IMFCC, MSRCC, NGCC, PNCC, PSRCC, PLP, RPLP, Frequency-stats*** etc. It also provides various filterbank modules (Mel, Bark and Gammatone filterbanks) and other spectral statistics.

Installation
============

Dependencies
------------

spafe requires:

-	Python (>= 3.5)
-	NumPy (>= 1.17.2)
-	SciPy (>= 1.3.1)

User installation
-----------------

If you already have a working installation of numpy and scipy, you can simply install spafe using pip:

```
pip install -U spafe
```

or conda (*not available at the moment*\):

```
conda install spafe
```

How to use
==========

Various examples on how to use spafe filter banks or feature extraction techniques are available under [examples](https://github.com/SuperKogito/spafe/tree/master/examples).

Contributing
============

Contributions are welcome and encouraged. To learn more about how to contribute to spafe please refer to the [Contributing guidelines](https://github.com/SuperKogito/spafe/blob/master/CONTRIBUTING.md)