Nkululeko 1.0: A Python package to predict speaker characteristics with a high-level interface

Nkululeko is a software to detect speaker characteristics by machine learning experiments with a high-level interface. The idea is to have a framework (based on e.g. sklearn and torch) that can be used to rapidly and automatically analyse audio data and explore machine learning models based on that data.

Some abilities that Nkululeko provides: combines acoustic features and machine learning models (including feature selection and features concatenation); performs data exploration, selection and visualization the results; finetuning; ensemble learning models; soft labeling (predicting labels with pre-trained model); and inference the model on a test set.

Nkululeko orchestrates data loading, feature extraction, and model training, allowing you to specify your experiment in a configuration file. The framework handles the process from raw data to trained model and evaluation, making it easy to run machine learning experiments without directly coding in Python.