This is the entry post for Nkululeko: a framework to do machine learning experiments on audio data based on configuration files.

Here's an overview on the tutorials:

• Introduction
• Nkulueko FAQ
• How to set up your first nkululeko project
• Setting up a base nkululeko experiment
• How to import a database
• Comparing classifiers and features
• Use Praat features
• Combine feature sets
• Classifying continuous variables
• Try out / demo a trained model
• Plot distributions of feature values
• Perform cross database experiments
• Meta parameter optimization
• How to set up wav2vec embedding
• How to soft-label a database
• Re-generate the progressing confusion matrix animation wit a different framerate
• How to limit/filter a dataset
• Specifying database disk location
• Add dropout with MLP models
• Do cross-validation
• Combine predictions per speaker
• Run multiple experiments in one go
• Compare several MLP layer layouts with each other
• Import features from outside the software
• Explore feature importance
• Plot distributions for feature values