README.md

Extraction of Audio Features for Speech Language Identification

This repository aims at feature extraction from WAV files.

The following features can be extracted:

• MFCCs
• Delta-MFCCs (1st and 2nd order)

Additionally, the following information is retrieved from the audio files:

• file name
• duration of the audio
• number of samples
• sampling rate

Python Version and Dependencies

It is recommended that you use Python 3.8 to set up your virtualenv (see setup section).

The following dependencies will be installed:

• librosa (0.8.0)

Setup

For the setup of this repository simply type:

make

This will

• set up a virtual environment for this repository,
• install all necessary project dependencies.

If this does not work, make sure you have the package virtualenv installed for your python interpreter (pip install virtualenv).

Extract Audio Features

To have features extracted from a series of WAV files, extract_mfcc.py takes a list of file names as an argument.

For example:

python3 extract/extract_mfcc.py path/file1.wav path/file2.wav

For all files in a directory:

python3 extract/extract_mfcc.py path/*

Clean and Re-install

To reset the repository to its inital state, type:

make dist-clean

This will remove the virtual environment and all its dependencies.
With the make command you can re-install them.

To remove temporary files like .pyc or .pyo files, type:

make clean