Voice Toolbox

The place to solve all your audio signal processing needs.

The current repo is under construction. Goal is to create a repository that contains all voice signal processing functions available from different open source projects and libraries, such as parsel mouth and librosa.

Files

To start: Setup a conda environment and run 'pip3 install -r requirements.txt' before running the available scripts.

Important: if you get an error with parselmouth make sure the installation is 'pip3 install praat-parselmouth'

The script for extracting features is parsel_process.py.

• To run: "python3 feature_extraction.py [sampling rate] [filepath] [output filepath] --[feature flag]"

feature flags: formants, ZCR, harmonics, rate_of_speech, loudness, pitch_features, spectral_features, energy

Features currently availabe:

1. Spectral Features:

• pitch
• pitch range
• spectral slope
• mel-frequency cepstral coefficients (MFCC)
• mean spectral roll-off
• median F0 (fundamental frequency)

2. Rate of Speech and loudness:

• max intensity
• mean intensity
• syllables per second
• pause rate
• energy

3. Harmonics

• harmonics to noise (HNR)
• Formants: f1,f2, f3, f4
• number of zero crossings (ZCR)

Extra Scripts for processed features

For visualization:

1. visualize_voice.py for all scatter plots along with other plotting features from praat.

• To run: 'python3 visualize_voice.py'

2. radar_plot.py for all radar plots

• To run: 'python3 radar_plot.py'

For PCA analysis of voice data: voice_pca.py is for PCA, RFE and Correlation plot:

• • To run: 'voice_pca.py'